M1: Monday, 12 September, 2016
08:15
M1
Chairs: Rob MacLeod and Leif Sornmo
Left Atrial Hypertrophy Increases P-Wave Terminal Force Through Amplitude but not Duration
Axel Loewe*, Robin Andlauer, Olaf Dössel, Gunnar Seemann and Pyotr G. Platonov
P-wave morphology correlates with the risk for atrial fibrillation (AF). Left atrial (LA) enlargement could explain both the higher risk for AF and higher P- wave terminal force (PTF) in ECG lead V1. However, PTF-V1 has been shown to correlate poorly with LA size. We hypothesize that LA hypertrophy, i.e. a thickening of the myocardial wall, also contributes to increased PTF-V1 and is part of the reason for the rather low specificity of increased PTF-V1 regarding LA enlargement. To show this, atrial excitation propagation was simulated in a cohort of four anatomically individualized models including rule-based myocyte orientation and spatial electrophysiological heterogeneity using the monodomain approach. The LA wall was thickened symmetrically in steps of 0.66 mm by up to 3.96 mm. Body surface ECGs were computed using realistic, heterogeneous torso models. During the early P-wave stemming from sources in the RA, no changes were observed. Once the LA got activated, the voltage in V1 tended to lower values for higher degrees of hypertrophy. Thus, the amplitude of the late positive P-wave decreased while the amplitude of the subsequent terminal phase increased. PTF-V1 and LA wall thickening showed a correlation of 0.95. The P-wave duration was almost unaffected by LA wall thickening (=2 ms). Our results show that PTF-V1 is a sensitive marker for LA wall thickening and elucidate why it is superior to P-wave area. The interplay of LA hypertrophy and dilation might cause the poor empirical correlation of LA size and PTF-V1.
PDF Abstract
M1: Monday, 12 September, 2016
08:15
M1
Chairs: Rob MacLeod and Leif Sornmo
Index of T-wave Variation as a Predictor of Sudden Cardiac Death in Chronic Heart Failure Patients with Atrial Fibrillation
Alba Martin*, Iwona Cygankiewicz, Antoni Bayés-De-Luna, Pablo Laguna, Enrico G Caiani and Juan Pablo Martinez
Aim: Chronic heart failure (CHF) together with atrial fibrillation (AF) are worldwide leading causes of morbidity and mortality in elders, where an important part of these deaths are due to sudden cardiac deaths (SCD). The high irregularity of ventricular response in AF patients makes the use of standard ECG-based SCD-risk markers inappropriate in this target population. The aim of this study was twofold: i) to propose a new index, suitable for AF patients, sensitive to ventricular repolarization changes; and ii) to evaluate its prognostic value in a population with CHF and AF. Materials and Methods: Holter ECG recordings from 176 consecutive CHF patients with AF, including 22 SCD events were analyzed (2 or 3 leads available, sampling frequency 200 Hz). The index of T-wave variation (ITV), quantifying the average T-wave changes in pairs of consecutive beats under stable rhythm conditions, was computed using a fully-automatic method based on the selective averaging technique. Survival analysis was performed considering SCD as an independent endpoint. Results: ITV was higher for SCD than for non-SCD victims (median (25th;75th percentile): 12.44 (7.21;42.71) µV vs 8.57 (5.63;14.08) µV, p=0.06). In a survival analysis where patients were classified as ITV(+) and ITV(-), setting the cut point at the third quartile of ITV values, ITV (+) outcome was successfully associated to SCD (Hazard Ratio (CI): 3.217 (1.365,7.581) per µV, p=0.008). Conclusion: In this study we have shown that ITV stratifies CHF patients with AF according to their risk of SCD, with larger T-wave variability associated to lower survival probability.
PDF Abstract
M1: Monday, 12 September, 2016
08:15
M1
Chairs: Rob MacLeod and Leif Sornmo
Modelling the Effects of Disopyramide on Short QT Syndrome Variant 1 in the Human Ventricles
Dominic G Whittaker*, Haibo Ni, Alan P Benson, Jules C Hancox and Henggui Zhang
Introduction: The short QT syndrome (SQTS) is a recently identified genetic disorder associated with ventricular and/or atrial arrhythmias and increased risk of sudden cardiac death. The SQTS variant 1 (SQT1) N588K mutation to the hERG gene causes a gain-of-function to IKr which shortens the ventricular effective refractory period (ERP), as well as reducing the potency of drugs which block the hERG channel. This study used computational modelling to assess the effects of disopyramide (DSP), a class 1a anti-arrhythmic agent, on human ventricular electrophysiology and re-entrant wave dynamics in SQT1. Methods: The O’Hara-Rudy dynamic (ORd) model of the human ventricular action potential (AP) was modified to incorporate a Markov chain model of IKr/hERG including formulations for wild type (WT) and SQT1 N588K mutant hERG channels. The blocking effects of DSP on IKr, INa, and ICaL were modelled using IC50 and nH (Hill coefficient) values from the literature, including different blocking potencies for IKr in WT and SQT1 mutant hERG channels. The ability of DSP to prolong the QT interval was evaluated using a 1D model of human ventricle with transmural heterogeneities and the corresponding pseudo-ECG. An idealised 3D left ventricular wedge model was also constructed in order to investigate the effects of DSP on re-entrant excitation wave dynamics. Results: Upon application of 10 µM DSP, which lies within the clinically-relevant range, the corrected QT interval in the SQT1 case was prolonged from 282 ms to 346 ms. Furthermore, this concentration of DSP increased the ventricular effective refractory period such that sustained re-entrant activity was no longer inducible in the left ventricular wedge model. Conclusion: We have used computational modelling to dissect ionic mechanisms of QT prolongation and anti-arrhythmic effects of DSP on SQT1 in the human ventricles. This study provides new insights into a potential pharmacological treatment in hERG-mediated SQTS.
PDF Abstract
M1: Monday, 12 September, 2016
08:15
M1
Chairs: Rob MacLeod and Leif Sornmo
Highest Dominant Frequency and Rotor Sites are Robust Markers for Atrial Driver Location in Non-invasive Mapping of Atrial Fibrillation
Miguel Rodrigo*, Andreu M Climent, Alejandro Liberos, Francisco Fernández-Avilés, Omer Berenfeld, Felipe Atienza and Maria S Guillem
Background: Inverse-computed Dominant Frequency (DF) and rotor maps have been proposed as non-invasive mapping techniques to locate atrial drivers maintaining atrial fibrillation (AF). This study evaluates the robustness of both techniques in localizing atrial drivers under the effect of electrical noise or uncertainties in the heart-torso structure. Methods: Anatomically realistic model of the atria within the torso was built. Inverse-computed DFs and phase maps were obtained on a population of 30 different mathematical AF simulations maintained by a single rotor and subjected to model variations. Simulated atrial highest DF (HDF) regions and rotor locations were compared with the same inverse-computed measurements following each variation: (i) ECG with white noise to the ECG (60-0 dB signal-to-noise ratio), (ii) linear (0-5 cm) or (iii) angular (0-45º) variation in the location and orientation of the atria inside the torso, or (iv) varying blood conductivity (0.5-9 S/m). Results: Individual inverse-computed EGMs showed a poor correlation coefficient of 0.45±0.12 with the actual EGMs in the absence of variations. The correlation coefficient worsened further to 0.22±0.11 with 10 dB noise, 0.01±0.02 with 3 cm displacement and 0.02±0.03 with 36º angular variation. However, inverse-computed HDF regions showed robustness in correlations against variations: from 82±18% match for the HDF region for the best conditions, down to 73±23% for 10 dB of noise, 77±21% for 5 cm displacement and 60±22% for 36º angular variation. The rotor location also presented a robust measurement: the distance from the inverse-computed rotor to the actual rotor was 0.8±1.61 cm for the best conditions, 2.4±3.6 cm for 10 dB of noise, 4.3±3.2 cm for 4 cm displacement and 4.0±2.1 cm for 36º. Conclusions: Localization of AF sources based on HDF and rotor location from non-invasive mapping is accurate even in the presence of noise and uncertainties in the atrial location or torso/blood conductance.
PDF Abstract
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Controlling the Inspiration/Expiration Ratio Benefits the Deceleration Capacity Index of Heart Rate in Assessing the Sympatho-vagal Balance
Qing Pan, Chenglong Gao, Gongzhan Zhou, Ruofan Wang, Yihua Yu, Luping Fang* and Gangmin Ning
Introduction: Deceleration capacity (DC) of heart rate is a novel index for evaluating the activity of the autonomic nervous system (ANS). We examined whether controlling the inspiration/expiration (I/E) ratio benefits the DC analysis based on a model-generated RR interval (RRI) database. A cardiovascular system model was adopted to simulate RRI time series. The model allows analyzing the role of sympathetic and vagal activities in the ANS. The respiratory pattern can be controlled in the model. Methods: Three hundred RRI time series with random sympathetic and vagal activities were simulated. According to the ratio between the sympathetic and vagal activities (S/V ratio), these subjects were categorized into a case group (S/V>1) and a control group (S/V<1). DC was computed for each subject. The performance of DC in distinguishing the two groups was examined by the receiver operating characteristic (ROC) analysis. The respiratory period is set to 6 s. The I/E ratio was controlled as 1:2, 1:1 and 2:1, respectively, and the performances of DC under different I/E ratios were compared. Results: The numbers of subjects in the case group and the control group are 161 and 139. With the I/E ratio as 1:2, 1:1, and 2:1, the mean area under the ROC curves (AUCs) of DC are 0.64, 0.74 and 0.75. DCs obtained with the I/E ratio of 1:1 and 2:1 have significantly larger AUCs than that obtained under the normal physiological I/E ratio of 1:2 (p<0.05). Conclusions: Controlling the I/E ratio above the normal physiological level renders a better ability of DC in assessing the sympatho-vagal balance.
Manuscript Pre-print
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Post-Stroke Alterations in Cardiovascular Responses and Heart Rate Variability during Orthostatic Challenge
Nandu Goswami*, Joel Rodriguez, Markus Kneihsl, Irhad Trozic, Rebecca Ruedl, Andreas Rössler, David A Green, Helmut Hingofer-Szalkay, Franz Fazekas and Andrew P. Blaber
Background: Older following stroke have a higher incidence of orthostatic hypotension, syncope and fall risk, which may relate to impaired autonomic responses limiting the ability to maintain cerebral blood flow. Thus, we investigated cerebrovascular and cardiovascular regulation in 10 elderly stroke patients (218 ± 41 days post-insult) and 13 age-matched healthy controls when sitting at rest and upon standing. We hypothesised that the stroke subjects on average would; 1) have a greater drop in arterial blood pressure upon standing, 2) take longer to re-establish normal stable blood pressure after standing; and 3) have less low-frequency (LF) heart rate variability (HRV) power spectra, indicative of sympathetic drive, upon standing. 4) attenuation of the spontaneous baroreflex response. Materials and Methods: Arterial blood pressure, heart rate and cerebral blood flow velocity were recorded while sitting for 5 minutes and then during quiet standing for 6 minutes. Results: In the seated position, the stroke group had significantly greater RR interval standard deviation (RRSD) (25.5 ± 13.6ms vs. 14.3 ± 7.4ms; p=0.024), which decreased upon standing (12.9 ± 10.9ms vs. 4.4 ± 7.7ms; p=0.041). Conclusions: The stroke group demonstrated altered HRV via significantly greater resting RRSD that decreased a greater magnitude upon standing. All other assessments of autonomic function showed no differences between both groups. These findings suggest that neuronal insult following could potentially result in attenuation of the autonomic responses to standing, but further investigation is needed to clarify the mechanisms behind increased likelihood of orthostatic hypotension, syncope and falls post-stroke.
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Analysis of Endocardial Micro-Accelerometry during Valsalva Maneuvers
Clément Gallet, Virginie Le Rolle, Jean-Luc Bonnet, Christine Henry, Albert Hagège, Philippe Mabo, Guy Carrault and Alfredo Hernandez*
Background: The analysis of cardiac mechanoacoustic signals has been shown to be useful for the evaluation of the cardiac mechanical function. A particular kind of cardiac mechanoacoustic signal, the endocardial acceleration (EA) signal, can be acquired by using a micro-accelerometer, embedded at the tip of a pacing lead, that may be chronically implanted inside a cardiac chamber. In our past works, we have proposed EA processing methods for the estimation of cardiac electro-mechanical parameters that have been applied to improve patient selection and to optimize device configuration in the context of Cardiac Resynchronization Therapy. In this work, we analyze the evolution of the main EA-derived markers during severe cardio-respiratory modifications. Method: ECG, intra-ventricular pressure and EA data obtained from the right ventricle, were acquired from 6 sheep during a set of Valsalva-like maneuvers comprising a baseline phase, a continuous positive pressure (CPP) phase and an apnea phase. Data have been processed offline to estimate the inotropic state and to segment the main EA components during each phase, in a beat-to-beat basis. Segmented EA components were further processed to extract the energy, the peak-to-peak amplitude and duration of each component. Results: The correlation between the energy of the EA1 component and the dP/dtmax is confirmed in this work. Significant differences were observed: i) on the mean instant of detection of EA2 during the baseline, CPP and apnea phases; ii) on the energy of EA1 (baseline vs. apnea) and EA3/4 (baseline vs CPP and baseline vs apnea) and iii) on the duration of the EA2 component during the three phases. Conclusion: The EA signal provides interesting information on cardio-respiratory dynamics, that may be useful to characterize respiratory events (apnea or hypopnea) from implantable devices. Moreover, this information may be useful to adapt the device therapy, according to the observed cardio-respiratory events.
Manuscript Pre-print
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Volatility Leveraging in Heart Rate: health vs disease
Ana Paula Rocha*, Argentina Maria Leite and Maria Eduarda Silva
Heart Rate Variability (HRV) data exhibit long memory and time-varying conditional variance (volatility). These characteristics are well captured using Fractionally Integrated AutoRegressive Moving Average (ARFIMA) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors, which are an extension of the AR models usual in the analysis of HRV. GARCH models assume that volatility depends only on magnitude of the shocks and not on their sign, meaning that positive and negative shocks have a symmetric effect on the volatility. Moreover, HRV recordings indicate further dependence of volatility on the lagged shocks. Thus, this work considers Exponential GARCH (EGARCH) models which assume that positive and negative shocks have an asymmetric effect (leverage effect) on the volatility, which copes with complex characteristics of the HRV data. ARFIMA-EGARCH models, combined with adaptive segmentation, are applied to 24 hour HRV recordings of 30 subjects from the Noltisalis database: 10 healthy (N), 10 patients suffering from congestive heart failure (CHF) and 10 heart transplanted patients (T). The results (mean ± sd) are for each group: long memory parameter d (0.44±0.06, N; 0.52±0.14, CHF; 0.76±0.10, T), percentage of segments with volatility (95.5±3.7, N; 81.7±11.5, CHF; 75.7±16.9, T), percentage of segments with leverage (81.7±13.1, N; 53.8±20.4, CHF; 41.9±12.8, T), volatility parameters u (0.28±0.07, N; 0.20±0.09, CHF; 0.21±0.13, T) and v (0.72±0.06, N; 0.64±0.18, CHF; 0.56±0.20, T) and leverage parameter w (0.18±0.11, N; 0.05±0.07, CHF; -0.01±0.02, T). The values indicate lower memory (d) in healthy subjects, as in previous studies. Diseased subjects present lower percentage of segments with volatility and leverage and also lower values for the volatility (u, v) and leverage (w) parameters. Overall, the results for the leverage parameter indicate that volatility responds asymmetrically to values of HRV under and over the mean.
PDF Abstract
Manuscript Pre-print
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Increased Systolic Blood Pressure driven Skeletal Muscle activation Following Stroke: A causality analysis
Nandu Goswami*, Ajay Verma, Amanmeet Garg, Da Xu, Reza Fazel Rezai, Kouhyar Tavakolian and Andrew P. Blaber
Background: Elderly individuals following stroke have a higher incidence of orthostatic hypotension, syncope and fall risk. Thus, in a pilot study we investigated the relationship between the arterial and skeletal muscle pump baroreflexes in 5 elderly (64.0 ± 4 yr) stroke patients (208 ± 14 days post-insult) and 5 age-matched healthy controls (61.4 ± 4 yr) during standing. We hypothesised that the stroke subjects would have attenuated baroreflex sensitivity (BRS), and increased reliance on skeletal muscle pump. Materials and Methods: The project received approval from the Ethics Committee of the Medical University of Graz. Simultaneous continuous non-invasive lower leg muscle activity (electromyography: EMG), 3-lead ECG and blood pressure were recorded continuously during the 5-minute stand portion of a sit-to-stand test. Subjects were instructed to breathe normally and when standing, to sway or shift their weight if they felt uncomfortable, but asked to stay as still and relaxed as possible, with their feet shoulder width apart Causality was analyzed between EMG and systolic blood pressure (SBP) in the last 4 minutes of standing. Data were segmented into a time window of 45 seconds, translated with an overlap of 5 seconds on the entire 4-minute data. Convergent cross mapping (CCM) was used for studying causality between the blood pressure and EMG signals. BRS was calculated using the sequence method. Statistical analysis was performed using repeated measures ANOVA. Results: Between the two groups there was no difference in spontaneous baroreflex (stroke: 4.5±1.1; control: 5.2±1.1 ms/mmHg; p=0.53) or EMG causality towards SBP (stroke: 0.71±0.05; control: 0.60±0.05, p=0.17). The causality relationship from SBP to EMG was greater in stroke patients (0.64±0.06) compared to controls (0.43±0.06, p=0.03). Conclusion: Although arterial baroreflex was not different between groups, elevated SBP to EMG activity suggests a potential compensatory action by the muscle pump towards blood pressure regulation following stroke.
S21: Monday, 12 September, 2016
10:00
S21
Chairs: Andrew Blaber and Sonia Gouveia
Sex Differences in Cardiac Autonomic Status during Autonomic Provocations
Marek Malik*, Katerina Hnatkova, Peter Smetana, Tomas Novotny and Georg Schmidt
Compared to men, women are known to have increased baseline vagal cardiac modulations. However, systematic data on sex differences during autonomic provocations are sparse. A population of 572 healthy subjects (279 females) aged 33.3±8.5 years, BMI 25.3±2.8 kg/m2 had repeated continuous 12-lead ECG recordings made during strict undisturbed supine, unsupported sitting, and unsupported standing position. Each position lasted at least 10 minutes of which data of 5 minutes stable heart rates (after at least 5 minutes of heart rate stabilization following position change) were used to calculate heart rate [HR] and quasi-normalized spectral components of heart rate variability. In women, the HR values at supine, sitting and standing were 69.7±8.64, 79.2±9.80, and 99.7±14.83 beats per minute [bpm], respectively. The corresponding HR values in men were 64.8±7.31, 74.1±9.02, and 93.2±14 .00 bpm, respectively. At all positions, the HR values were significantly different between women and men. Thus, while as expected, women had HR approximately 5 bpm faster than men, in both sex groups, HR increased by approximately 10 bpm from supine to sitting, and by approximately 30 bpm from supine to standing in both sexes. In women quasi-normalized HF components of HRV [HF/(HF+LF) expressed in percent] at supine, sitting, and standing were 43.4±17.18, 32.1±16.58, and 20.0±11.91, respectively. In men, the corresponding values were 35.9±15.69, 24.9±14.44, and 18.9±12.77, respectively. Highly statistically significant differences between women and men were present at supine and sitting but not at standing. The change from supine to sitting was approximately 11 percent in both sexes but the change from supine to standing was 23 percent in women and 17 percent in men. On postural provocation, cardiac vagal modulations in women are thus suppressed much more than those in men. Substantial differences in cardiac autonomic regulation therefore exist between both sexes.
S22: Monday, 12 September, 2016
10:00
S22
Chairs: Simon Rabkin and Cadathur Rajagopalan
Postextrasystolic T Wave Change to Stratify Risk of Pump Failure Death in Patients with Chronic Heart Failure
Gustavo Lenis*, Robert Menges, Julia Ramírez, Iwona Cygankiewicz, Antoni Bayés de Luna, Juan Pablo Martínez, Pablo Laguna and Olaf Dössel
The postextrasystolic T wave change (PEST) is an electrocardiographic phenomenon in which the morphology of the normal T wave is altered for a short time after a ventricular ectopic beat (VEB). It has been observed in patients with other cardiac pathologies but it has not been proposed as a risk index for cardiac death. Since PEST seems to be potentiated in patients with depression of myocardial contractility, we hypothesize that PEST could be used to predict pump failure death (PFD) in patients with chronic heart failure (CHF). For the purpose of quantifying PEST, the parameters morphological change onset (MCO) and morphological change slope (MCS) were introduced. MCO describes an initial morphological change of the T wave after a VEB, while MCS is responsible for the description of the restitution to its original shape. An example of how the quantification of PEST is carried out for a patient in the MUSIC database can be seen in the figure. 537 records from the MUSIC study were separated according to their cause of death and comparisons against the others (including survivors) were carried out. In addition, receiver operating characteristic (ROC) curves were used to determine the optimal separating thresholds for MCO and MCS that maximized the sum of sensitivity and specificity for PFD risk prediction. The results showed that no significant differences could be established and the proposed parameters do not seem to be related to any kind of cardiac death. In future, other forms of PEST quantification together with more databases can be used to definitely conclude that PEST has no predictive power.
PDF Abstract
S22: Monday, 12 September, 2016
10:00
S22
Chairs: Simon Rabkin and Cadathur Rajagopalan
Automated ECG Ventricular Beat Detection with Switching Kalman Filters
Julien Oster* and Lionel Tarassenko
The explosion of clinical data, and especially physiological recordings such as ECG, creates a real need for highly accurate and fully automated analysis techniques. An automated detection of ventricular beat is proposed, which is an extension of a recently published switching Kalman filter (skf) approach. The latter technique enables automatic selection of the most likely mode (beat type), and makes novelty detection possible by incorporating a mode for unknown morphologies (X-factor). The previously published technique is semi-supervised and relies on the manual annotation of the different clusters (or modes), thus making it less readily applicable in Big Data scenarios. Here we propose to extend the switching Kalman filter technique by automating the labeling of the modes. Each heartbeat in a mode was classified individually using a feature-based approach, and the cluster was assigned a given type by majority voting. Two different feature-based classifications were tested. First, ecgkit, a state-of-the-art toolkit recently made available online provide an heartbeat classification based on clustering and Linear Discriminant Analysis. Second, a Support Vector Machine (svm) approach was used with the same features (than ecgkit). Therefore two different automated switching Kalman filter techniques were tested, ecgkit-skf and svm-skf, that differed only by the way the modes were classified. Both approaches were assessed on an independent subset of the MIT-BIH arrhythmia database (22 individual subjects, 30-minute recordings), and were compared to the semi-supervised switching Kalman filter approach (skf), as well as to the classification techniques, ecgkit and svm. F1 varied from 81.2% for ecgkit, 85.4% for svm, 91.8% for ecgkit-skf, 92.3% for svm-skf, and 98.6% for skf. The proposed combined techniques demonstrated improved automatic beat classification, compared to state-of-the-art fully automatic techniques (ecgkit). Performances were however still lower than what was achieved with semi-supervised techniques (skf), highlighting the fact that some clusters were mislabeled.
Manuscript Pre-print
S22: Monday, 12 September, 2016
10:00
S22
Chairs: Simon Rabkin and Cadathur Rajagopalan
Temporal Alignment of Asynchronously Sampled Biomedical Signals
Samuel Emil Schmidt*, Kasper Emerek, Ask Schou Jensen, Jacob Melgaard, Kasper Sørensen, Claus Graff, Peter Sogaard and Johannes Jan Struijk
Temporal alignment of signals obtained using different acquisition systems is often complicated by asynchronous sampling. Especially in long recording sequences, drifting clocks result in varying delays between signals. In the current example we aligned 3-lead ECGs recorded in a phonocardiogram setup with 12-lead Holter ECGs. Methods: Two signals with common morphology (lead II from both devices, recorded synchronously with closely placed electrodes) were resampled to approximately similar sample rates. An initial alignment was obtained using cross-correlation analysis. Delays were estimated between short subsegments of one signal with the full length of the other. The median delay was then used for a coarse alignment of the two signals. Next, instantaneous delays were estimated using cross-correlation analysis of the two signals in a running window of four seconds duration. The first derivative of the instantaneous delays is related to the variation in sample rate between signals. Consequently, a smoothed version of this derivative was used for local resampling of one of the signals before final alignment. We validated the current method by visual inspection of the alignment between the 3-lead and 12-lead ECGs in 15 recordings of at least 45 minutes duration. In addition, the delay between R-peaks in the two signals was measured in windows of 10 seconds in the beginning, middle and end of each recording. Results: Visual inspection confirmed that all recordings were synchronized by the alignment procedure. The mean and standard deviation of the delay between R-peaks in the synchronized ECGs was 0.5±5.7 ms. Conclusion: We present a fully automated method for alignment of signals sampled asynchronously with drifting clocks.
Manuscript Pre-print
S22: Monday, 12 September, 2016
10:00
S22
Chairs: Simon Rabkin and Cadathur Rajagopalan
Comparison of two methods for assessment of Microvolt T-Wave Alternans: discrete vs continuous T-wave analysis
Thaís Winkert*, Paulo Roberto Benchimol-Barbosa and Jurandir Nadal
Micro T-wave alternans (MTWA) is a risk marker for life threatening ventricular tachyarrhythmia. Classically, MTWA is assessed by quantification of beat-by-beat Twave amplitude alternation. This method requires accurate determination of T-wave peaks (discrete method) to create a sequence of T-wave amplitude series, which undergoes spectral analysis using the fast Fourier transform (FFT) for analysis. The need of precise measurements of T-wave amplitudes turns this method sensitive to noise. To overcome this limitation, a new method was developed, based on Hilbert Transform of the T-wave morphology series (continuous method). To accomplish this task, a 300 ms window containing the T-wave of every beat was isolated, and concatenated to form an artificial and continuous signal with T-waves. The Hilbert Transform was then applied to calculate the envelope of this signal. The alternans was detected after FFT of the envelope, as a peak on the frequency that corresponded to half of the main signal frequency. Both methods were tested in 50 ECG signals of Physionet T-Wave Alternans Database, 31 synthesized and 19 real world signals. The comparisons of the methods were carried out by linear correlation test, Wilcoxon test, and Bland-Altman charts, in channels 1 and 2. There was no significant differences between both methods in all tests, either synthesized or real world signals. The novel continuous method to quantify micro T-wave alternans based on whole T-wave morphology is feasible, accurate and reproducible, and have potential clinical application.
S22: Monday, 12 September, 2016
10:00
S22
Chairs: Simon Rabkin and Cadathur Rajagopalan
An Index for T-wave Pointwise Amplitude Variability Quantification
Julia Ramírez*, Michele Orini, J. Derek Tucker, Esther Pueyo and Pablo Laguna
Background: The comparison between the pointwise amplitude of different T-waves provides insight into ventricular repolarization liability, but there might be physiological variability present in the time-domain of such T-waves, like heart rate changes or increased repolarization heterogeneities, that may corrupt the measurement of amplitude variability. This motivates the seek for a robust marker of T-wave pointwise amplitude variability, independent from the underlying time-domain variability. Methods: We, first, studied the performance for removing time-domain variability (warping) of two algorithms, one using the original and another one using transformed T-waves (SRSF). We, next, compared the robustness against additive Laplacian noise of two markers, $d_y$ and $d_a$, of T-wave pointwise amplitude variability, after compensating for the underlying temporal variability with the preferred warping algorithm. $d_y$ was obtained from the transformed T-waves while $d_a$ was proposed in this work and was derived from the original T-waves. We finally used the most robust marker to measure the T-wave pointwise amplitude variability, between every T-wave recorded during a Tilt test and their mean T-wave, in a database of 17 healthy subjects. Results: The preferred warping algorithm was the SRSF because it is not affected by differences between the amplitudes of the original T-waves. Besides, the marker $d_a$ showed lower relative error values than $d_y$ for every level of noise. The analysis of actual electrocardiogram records proved that $d_a$ was significantly lower during the tilt than in supine position (-5.5 $\%$ vs 6.5 $\%$, p<0.01). Conclusions: The proposed marker, $d_a$, robustly quantified physiological variabilities of the T-wave amplitude, showing its potential to be used as an arrhythmic risk predictor in future clinical situations.
PDF Abstract
S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Cardiac Imaging and Modeling: Predicting the Future
Ravi Ranjan*
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S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Subject-Specific Detection of Ventricular Tachycardia Using Convolutional Neural Networks
Sandeep Chandra Bollepalli, S Sastry Challa and Soumya Jana*
Aim: Onset of ventricular tachycardia (VT) is clinically signi?cant, including as a trigger to de?brillator implants. We propose a reliable technique to detect such onset using convolutional neural network (CNN). Method: The proposed CNN adds convolution and pooling layers below the input layer and above the hidden and output layers of usual neural network (NN). While traditional methods, such as NN and support vector machine (SVM), operate on ad hoc features, our additional layers learn suitable linear features from training data, providing an advantage. In the above ?gure, learned ?lters, and their outputs (features) for normal sinus rhythm and VT are depicted. Results: Taking Creighton University ventricular tachyarrhythmia database, the baseline wander was removed, and overlapping signal vectors, each of duration 5s, were formed. Altogether, the 35 patient records amounted to 22,772 such vectors. Three experiments were performed, where the respective training data consisted of (subject-oblivious) a random 80% of all signal vectors; (unseen subject) signal vectors from a random 28 subjects (80%); and (subject-speci?c) signal vectors from a random 28 subjects and suitable 20% duration of rest of the subjects. In each case, remaining vectors were used for testing. Each experiment underwent 100 independent trials, and mean and standard deviation of sensitivity (Se), speci?city (Sp) and accuracy (Acc) are reported in the table. Contribution: We (i) adopted a subject-speci?c approach recommended by ANSI/AAMI EC57: 2012 for VT detection, and compared with subject-oblivious (optimistic) and unseen subject (conservative) experiments; (ii) learned features using CNN instead of using ad hoc ones; and (iii) achieved high mean performance as well as high robustness (standard deviations two orders of magnitude lower compared to existing methods).
PDF Abstract
S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Enhancement of Life-threatening Arrhythmias Discrimination in the Intensive Care Unit with Morphological Features and Interval Features Extraction via Random Forest Classifier
Farhad Asadi, Mohammad Javad Mollakazemi, Shadi Ghiasi* and S. Hossein Sadati
Introduction: Intelligent patient monitoring has continued to enhance and develop in hospitals from early stage of monitoring systems. So, practical medical monitoring devices to react to patient conditions and also detect unwanted clinical conditions are very important. Aims: Our algorithm uses pulsatile waveforms and simultaneous ECG and the aims of the proposed algorithm is the detection and enhancement for determination of the life threatening arrhythmia alarms in the context of the PhysioNet 2015 Challenge. Methods: our analysis steps included: In our algorithm, features for training the random forest classifier (RFC) were derived from applying the signal quality assessment to both pulsatile signals and ECG signal too. Primarily, preprocessing step was done by applying the band pass filters to multiple sources, such as alterial blood pressure (ABP), photoplethysmogram (PPG) and electrocardiogram (ECG) and then heart beat detection through the adaptive threshold were determined. The SQI approach for the pulsatile signals were applied through the ppgSQI and the jSQI algorithms and also spectral and statistical features was extracted for ECG channel as well. In a next process, the heuristic thresholding of each ABP pulse are estimated with the function of abpfeature and also heart rate (HR) features from the ECG and pulsatile signals in a segment before the alarm was extracted and computed. Also, for assessing regularity of the beats, inter-beat intervals for pulsatile waveforms and also checking the frequency maxims for better suppression of ventricular flutter/fibrillation in the ECG channel were computed. Finally, RFCs were trained with arrhythmia features set for every type of the arrhythmia. Results: our algorithm was trained with the use of 750 records provided by PhysioNet dataset for the challenge of 2015 and according to the types of arrhythmia, our overall scores varied. Our average score for our best performance for all the alarms in terms of ture positive were 67% and for true negative were 77% and for false negative were 1.8%.
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S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Nonlinear Energy Operators for Defibrillation Shock Outcome Prediction
Beatriz Chicote Gutiérrez, Unai Irusta Zarandona*, Elisabete Aramendi Ecenarro, Iraia Isasi Liñero, Daniel Alonso Moreno, Fernando Vicente Casanova and Maria de las Cruces Sanchez Fernandez
Aim: To predict defibrillation success by the local analysis of the energy content of the pre-shock ventricular fibrillation (VF) waveform acquired by automated external defibrillators (AED). Accurate prediction of shock success would avoid futile defibrillation attempts that may damage the myocardium, and would help optimizing treatment decisions for out-of-hospital cardiac arrest (OHCA) patients. Materials: Data came from 163 OHCA cases treated by the Emergency Medical Technicians of the Basque Health Service between 2013 and 2015. Patients were treated with different AED models, but all ECGs were resampled to fs=250 Hz. Shocks were considered successful if sustained QRS complexes (rate>30min-1) appeared within one minute. The dataset had 107 successful and 312 unsuccessful shocks. Methods: A Smoothed Nonlinear Energy Operator (SNEO) was applied to 5 second pre-shock VF waveform segments, and its median value was used to predict shock success. Smoothing Kaiser windows of different lengths (L) and shape factors (beta) were used to adjust to typical windows. Performance was evaluated in terms of balanced error rate (BER) to equally weight Sensitivity (Se) and Specificity (Sp). Results were compared with typical predictors based on time, slope or spectral analysis. Finally, the analysis segment duration was shortened to determine the minimum for an accurate prediction. Results: The best results were obtained for L=8 and beta=9. The minimum BER was 0.22 with Se 81% and Sp 75%. The best time, slope end spectral features had a BERs of 0.24 (Se/Sp of 78/73%), 0.24 (Se/Sp of 78/74%) and 0.26 (Se/Sp of 71/77%), respectively. For pre-shock segments as short as 2-second the BER was under 0.25. Conclusions: The median value of SNEO is an accurate shock outcome predictor, even for VF-segments as short as 2 second.
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S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Additive Model to Evaluate the Accuracy of Chest Compression Feedback Systems in Moving Vehicles
Digna M González-Otero*, Jesús Ruiz, Sofía Ruiz de Gauna, James K Russell, Luis Alberto Leturiondo and Purificación Saiz
Introduction: Chest compression quality affects survival from cardiac arrest. For optimal results, feedback devices can be used to guide chest compression depth and rate. Most devices analyze chest acceleration during CPR, and thus could be inaccurate when used in moving vehicles. Accuracy could be assessed by providing chest compressions to a sensorized manikin in the moving vehicle and comparing the computed feedback parameters with a gold standard. However, this solution may be difficult to implement in certain vehicles. Aim: To develop an additive model to evaluate the accuracy of accelerometer-based CPR feedback devices in moving vehicles and to apply it to the case of a plane. Materials and Methods: A resuscitation manikin was equipped with a displacement sensor for chest compression depth and rate reference. Twenty volunteers provided chest compressions to the manikin in the laboratory (static conditions) during 1-min episodes with a tri-axial accelerometer placed beneath their hands. Target rate was 100 compressions per minute (cpm) and target depth 5 cm. Tri-axial acceleration of a plane (dynamic noise) was measured during the trips Bilbao-Munich and Frankfurt-Bilbao. The acceleration that would have been measured by a feedback device used in a plane was modeled as the sum of the acceleration measured in static conditions and the dynamic noise acquired in the plane. Accuracy of a CPR feedback algorithm was evaluated both in static conditions and when applying the additive model. Results: In static conditions, median (P_25, P_75) unsigned error in depth and rate estimation were 1.4 (0.6, 2.3) mm and 0.9 (0.4, 1.5) cpm, respectively. When adding dynamic noise of the plane, errors were 1.6 (0.7, 2.9) mm and 0.9 (0.4, 1.5)cpm. Conclusions: The additive model simplifies evaluating the accuracy of CPR feedback devices in moving vehicles. In the evaluated conditions, the algorithm was accurate and could be safely used.
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S23: Monday, 12 September, 2016
10:00
S23
Chairs: Ravi Ranjan and Sofía Ruiz de Gauna
Chest Diameter Measurement in Pediatric Patients for Chest Compression Feedback Calibration
Sofía Ruiz de Gauna*, Digna M González-Otero, Jesús Ruiz, Stefano De Nigris, Purificación Saiz, José Julio Gutiérrez, James K Russell and Elena De Momi
Introduction: During cardiopulmonary resuscitation (CPR), rescuers should provide high-quality chest compressions to the victim. For adults, target depth is fixed (between 5 and 6cm), and feedback devices, usually based on accelerometers, can be used to guide the maneuver. For pediatric patients, conversely, target depth is one third of the antero-posterior diameter of the chest, and thus varies depending on patient age and morphology. Aim: To develop an algorithm to estimate chest diameter in pediatric patients using accelerometers. Materials and Methods: Five volunteers participated in the data collection. Using a tri-axial accelerometer, we measured the accelerations generated when moving the sensor from the floor to different heights (8, 10, 12, 14, and 16\,cm), that simulated chest diameter. Two records were generated per volunteer and height. A total of fifty records were acquired. Chest diameter was measured by applying double integration to the acceleration in the z axis (perpendicular to the chest). First, acceleration was calibrated and gravity was subtracted. Second, the trapezoidal rule was applied to integrate the acceleration from the instant in which the movement began, t_i. This instant was identified by applying a threshold to the acceleration. Third, the resulting signal (velocity) was band-pass filtered, and the trapezoidal rule was applied once again to compute the displacement signal. Finally, chest diameter was identified as the displacement value at the instant in which the movement finished, t_e, identified as a zero-crossing point in the velocity. Results: Median (P_25, P_75) unsigned absolute and relative errors were 0.9 (0.3, 1.9)cm and 9.2 (2.5, 14.6)%, respectively. This would imply an error in the target depth (one third of the chest diameter) below 6.5 mm in 75% of the cases. Conclusions: The proposed algorithm could be used to calibrate CPR feedback devices for pediatric patients.
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S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
Aortic Flow and Morphology Adaptation to Deconditioning after 21-Days of Head-Down Bed-Rest Assessed by Phase Contrast MRI
Enrico Caiani*, Giovanni Riso, Federica Landreani, Alba Martin, Selene Pirola, Filippo Piatti, Francesco Sturla, Pierre Vaida and Pierre-Francois Migeotte
Aims. Prolonged immobilization generates cardiac deconditioning, a risk factor for cardiovascular disease. Our aim was to assess the effects of 21-days of strict head-down (-6 degrees) bed-rest (BR) deconditioning, and effectiveness of reactive sledge jump countermeasure (CM) daily application, on ascending aortic flow by Phase Contrast (PC) MRI, capable to provide in vivo quantitative blood flow assessment. Methods. Twenty-four healthy men (mean age 28±6) were enrolled, and assigned to control (CTRL, N=12) or countermeasure (CM, N=12) group. The experiment was conducted at DLR (Koln, Germany) as part of the European Space Agency BR studies. PC-MRI images (Symphony 1.5T, Siemens) with interleaved three-directional velocity encoding (VENC: x and y: 80 cm/s; z: 150 cm/s) were obtained transecting the ascending aorta, on top of the aortic root (spatial resolution 1.4 x 1.4 mm2), before and after 21-days of BR. The resulting planar magnitude data and three-directional velocities were imported into a previously validated in-house segmentation and data analysis tool. In particular, semi-automated region growing and thresholding, exploiting texture properties, were applied to segment the lumen, thus providing the region in which to limit the computation of the following fluid-dynamic parameters from velocity images: area lumen (AL), flow velocity, stroke volume (SV), flow rate (Qpeak), time-to-peak flow, systolic duration and heart beat duration (RR). Results. After 21 days, in CTRL significant decreases in SV (14%), Qpeak (5%) and AL (4%) were observed compared to baseline values. Conversely, for CM no changes were observed in these parameters, but only in RR (-8%) and time-to-peak flow (+6%). Conclusions. Cardiac adaptation to deconditioning due to immobilization resulted in a reduction of SV and Qpeak that might have induced a remodeling process in the ascending aorta, by shrinking of its lumen. The applied CM seemed to counteract these effects.
S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
Development of 3D Patient-specific Models for Left Atrium Geometric Characterization to Support Ablation in Atrial Fibrillation Patients
Maddalena Valinoti*, Claudio Fabbri, Dario Turco, Roberto Maantovan, Antonio Pasini and Cristiana Corsi
Introduction. Radiofrequency catheter ablation (RFA) is an important and promising therapy for atrial fibrillation (AF) patients. About 50% of patients present AF recurrence during the first three months of follow-up. Several studies have been performed to assess the relationship between left atrium (LA) volume and AF recurrence following RFA. In fact, atrial enlargement is a consequence of AF and may facilitate AF induction. The aim of this study was to develop a unified workflow for LA segmentation from magnetic resonance angiography to provide (1) a 3D patient-specific LA model without pulmonary veins (PVs) in order to characterize LA size and (2) a 3D patient-specific model including PVs to assist RFA procedure. Methods. Eleven patients were enrolled in the study. A fully automated edge-based level set approach guided by a phase-based edge detector was developed for LA segmentation. A 3D LA patient-specific model with PVs geometry was obtained from 2D contours. The subsequent PVs deletion was obtained by applying thinning morphological operators and by removing the spurious segments corresponding to the PVs. Atrial volume estimates were computed and validation was performed by comparison with volumes derived from manual tracing by an expert radiologist. Results Automatic segmentation was feasible in all patients. Linear regression and Bland-Altman analyses resulted in very good agreement between LA volume estimates and reference values (y=0.92x+4.9, r=0.97, bias=-1.8ml (-2.1%), SD=5.6ml (6.5%)). Mean percentage difference was -1.8%±7.4% (abs value: 5.9%±4.4%). Conclusion. A unified and fast workflow for the development of 3D patient-specific LA models was presented. A more realistic LA anatomy provided by the 3D patient-specific LA model with PVs could support RFA procedure by the integration with voltage information. The 3D patient-specific LA model without PVs could allow accurate LA size characterization providing better understanding of the link between LA volume and AF recurrence.
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S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
Automatic Segmentation of Left Ventricular Myocardium by Deep Convolutional and De-convolutional Neural Networks
Xulei Yang*, Like Gobeawan, Si Yong Yeo, Wai Teng Tang, Zhen Zhou Wu and Yi Su
Motivations: Deep learning has been integrated into several existing image segmentation methods to yield impressive accuracy improvement for LV endocardium segmentation. However, challenges remain for segmentation of LV epicardium due to its fuzzier appearance. In this work, we develop a deep learning method to segment the whole LV myocardium from cardiac magnetic resonance (CMR) in one step, i.e., to derive the endocardium and epicardium simultaneously. Methodology: A deep convolutional network was constructed on the Caffe deep learning platform. It consists of 5 convolutional layers, 2 pooling layers, and 2 de-convolutional layers. The layer parameters are trained using myocardium-annotated CMR datasets from 33 subjects. A new loss function based on the dice coefficient similarity was designed for training the network. This allows even the smallest myocardium to be recognized on a large CMR image background. Of the total 5,011 frames, 3,229 frames were used for network training, 861 frames were used for validation, and 921 frames were used for testing. The training took around 2.7 hours to complete (40,000 iterations), while the subsequent myocardium segmentation took 0.044 second per frame. Results: We evaluated the performance of our deep convolutional net-work by comparing the segmented areas with the manually segmented ones in terms of Dice metrics (DM) - a DM value between 0 and 1 indicates the degree of overlap normalized against the union of the auto- and manually-segmented areas. Without any further post-processing, the average DM for the 921 test frames was 0.72. Conclusions: In its current form, the proposed one-step deep learning method cannot compete with state-of-art myocardium segmentation methods. Nevertheless, it delivers promising first pass segmentation results. Moving ahead, we aim to develop a hybrid method by fine-tuning deep neural networks, augmenting training samples, and post-processing broken myocardium segmentations using state-of-art techniques.
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S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
Right Ventricular Endocardial Segmentation in CMR Images using a Novel Inter-Modality Statistical Shape Modelling Approach
Concetta Piazzese, M. Chiara Carminati, Rolf Krause, Angelo Auricchio, Lynn Weinert, Gloria Tamborini, Mauro Pepi, Roberto M. Lang and Enrico G. Caiani*
INTRODUCTION. Statistical shape modelling (SSM) approaches have been proposed as a powerful tool to segment the left ventricle in cardiac magnetic resonance (CMR) images. Extending it to segment the right ventricle (RV) is not an easy task, due to the highly variable RV shape from apex to base, thin and often indistinguishable myocardial walls and presence of trabeculations. We developed a new inter-modality SSM method to segment the RV cavity in CMR images and validate it compared to the conventional gold-standard (GS) manual tracing. METHODS. A database of 4347 intrinsically 3D surfaces, obtained segmenting the RV from transthoracic 3D echocardiographic (3DE) images throughout the cardiac cycle in 219 retrospective patients, was used to train a RV SSM. Manual initialization of four points (two for tricuspid valve leaflet insertion, one for RV apex and one for the aorta) was performed to derive the initial pose and scaling factor of the SSM inside the stack of short-axis (SAX) CMR images. The detection process consisted in iteratively align and globally deform the SSM on the base of some features extracted, with different strategies, from each SAX plane until a stable condition was reached. RESULTS. Algorithm segmentation was feasible in 14 CMR patients, with an average time of 1 minute per patient. The comparison of volumes with GS showed high correlation (r2 = 0.97). Bland-Altman resulted in a significant bias (+9.3 ml) and narrow limits of agreement (± 9% error) . Also, point-to-surface distance resulted in 1.94 ± 0.35 mm. CONCLUSIONS. A novel application of SSM trained on intrinsically 3D RV endocardial surfaces extracted from 3DE images and applied to segment the RV cavity in SAX CMR images was proposed. Preliminary results showed this approach to be fast and accurate in segmenting the RV endocardium.
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S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
A Bi-centric Study of Myocardial Circumferential Strain from CMR by Using Hyperplastic Wrapping Approach
Hua Zou, Ce Xi, Xiaodan Zhao, Ju Le Tan, Lik Chuan Lee, Kenneth Guo, Martin Genet, Fei Gao, Ru San Tan, Jun-Mei Zhang* and Liang Zhong
Introduction Hyperelastic warping is an image based finite element (FE) analysis of the regional strains for the assessment of the cardiac deformation. Recently, a novel program based on the hyperelastic warping approach was developed to analyse the circumferential strains of the whole heart: left ventricle (LV), right ventricle (RV) and the septum. This study aimed to study the reproducibility of this approach in obtaining the circumferential strains of the LV, RV and the septum. Methods 10 patients were enrolled and underwent standard CMR scan (3T Philips scanner). Whole heart models (i.e. including LV, RV, and the septum) were reconstructed by using the following steps: 1) contour delineation; 2) surface generation; 3) mesh generation; 4) material region partition; 5) fibre orientation assignment; 6) deformable image registration through the hyperelastic warping approach; 7) circumferential strain calculation. The models were re-constructed and the circumferential strains were calculated by two independent investigators from NHCS (ZH) and MSU (CX). Coefficient of determination of R2 values were computed for the comparison of circumferential strain produced by each investigator. Results There were good correspondence between two investigators, with the R2 values for RV circumferential strain (y=1.0054x-0.0004; R2 =0.9471, p<0.0001), LV circumferential strain (y=0.958x-0.0118, R2=0.9433, p<0.0001) and septum circumferential strain (y=1.089x+0.004, R2 =0.9382, p<0.0001) respectively (see Figure 1). The bias of circumferential strain in RV, LV and septum are 0.000708±0.01597, 0.006886±0.008246 and 0.002778±0.006562. No significant bias and narrow limits of agreement were observed. Conclusions The study demonstrated that the hyperelastic warping was able to provide strain computation of systolic contraction of the right ventricle, left ventricle and septum.
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S24: Monday, 12 September, 2016
10:00
S24
Chairs: Victor Mor-Avi and Carolina Vallecilla
A Novel Left Ventricular Volumes Prediction Method Based on Deep Learning Network in Cardiac MRI
Gongning Luo*, Guanxiong Sun, Kuanquan Wang, Suyu Dong and Henggui Zhang
Aims: Accurate estimation of left ventricular (LV) volumes plays an essential role in clinical diagnosis of cardiac diseases using MRI. Conventional methods of estimating ventricular volumes depend on the results of manual or automatic segmentation of MRI. However, manual segmentation of MRI sequences is extremely time-consuming and subjective, and automatic segmentation is still a challenging task. Therefore, this study aims to develop a new LV volumes prediction method without segmentation, motivated by the Second Annual Data Science Bowl from Kaggle (SADSB) in 2016. Methods: The proposed method is based on a deep learning framework, which includes a convolution network of five layers for features representation, and a full connection network of three layers for prediction. The two kinds of features (Gabor features and intensity) from multi-orientation (apex, mid, and base slices from short axis, four chambers slice and two chambers slice from long axis) images are used for initial inputs, and the outputs of the network are the end-diastolic and end-systolic volumes (EDV, ESV). The deep learning network was trained and tested on cardiac MRI datasets from SADSB including 1140 patients (500 train patients and 640 test patients). At last, the proposed method was evaluated by the recognized criterion in this field, including the linear regression fit (y = ax + b, ideally a = 1 and b = 0), correlation coefficient (R) and mean errors (ME) for EDV, ESV and ejection fraction (EF). Results: The clinical indexes predicted by our method were compared with ground truth from SADSB, and the results are as following: EDV: y=0.91x+11.7, R=0.95, ME=5.1±3.1ml; ESV: y=0.97x+9.5, R=0.92, ME=3.6±2.7ml; EF: y=0.87x+0.2, R=0.9, ME=6.1±4.1%. Conclusion: The proposed LV volumes prediction method based on deep learning has been proved accurate and effective.
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S31: Monday, 12 September, 2016
11:45
S31
Chairs: Marek Malik and Luca Mainardi
Curvatures of QRS/RR Relationship in Healthy Individuals
Katerina Hnatkova, Peter Smetana, Ondrej Toman, Georg Schmidt and Marek Malik*
The relationship between QRS duration and underlying heart rate is known to be individual-specific with intra-subject stability and inter-subject differences. Nevertheless, the pattern of the QRS/RR profiles has not been studied in detail. QRS duration and its heart rate dependency were evaluated in 420,615 electrocardiograms (ECG) from 523 healthy subjects (mean age 33.4±8.4 years, 254 women). QRS durations were measured under careful visual control in superimposed representative complexes of all 12 ECG leads. The measurements were made at stable heart rates. In each subject, the relationship between QRS duration and underlying heart rate was modeled by a curve-linear regression QRS[i]=A+D(1-RR[i]^G)+e[i] where QRS[i] and RR[i] are individual QRS measurements with RR intervals (in seconds) representing underlying heart rate, and where A is a subject-specific QRS duration at RR of 1 second, G is the curvature of the QRS/RR relationship, D/G is the slope of the relationship (note that the derivative of x^g equals to g at x=1), and e[i] are normally distributed zero-centered errors. The regression residuals of this curve-linear regression were compared with those of linear regression. As expected, QRS durations at RR=1s were shorter in women compared to men (98.7±5.6ms vs 103.3±5.9ms, p<0.00001). The curve-linear QRS/RR regression residuals were also lower in women compared to men (1.18±0.59 vs 1.37±0.60ms, p=0.0001) and substantially smaller than the linear regression residuals (5.99±5.02 and 6.91±5.86ms in women and men, respectively). In both sexes, the curve-linear residuals correlated with QRS durations at RR=1s (r2=0.34 and r2=0.32 in women and men, respectively). While the QRS/RR slopes did not differ between women and men, the non-linear patterns were significantly more curved in women compared to men (-3.22±12.58 vs -1.2±9.3, p=0.038). Thus the QRS/RR patterns are not only highly non-linear in healthy subjects but also more curved in women compared to men.
S31: Monday, 12 September, 2016
11:45
S31
Chairs: Marek Malik and Luca Mainardi
The Effects of 40 Hz Low-pass Filtering on the Spatial QRS-T Angle
Daniel Guldenring*, Dewar Finlay, Raymond Bond, Alan Kennedy and James McLaughlin
The spatial QRS-T angle (SA) is a vectorcardiographic (VCG) parameter that has been identified as a marker for changes in the ventricular depolarization and repolarization sequence. The SA is defined as the angle subtended by the mean QRS vector and the mean T vector of the VCG. The SA is typically obtained form VCG data that is derived from resting 12-lead ECG. Resting 12-lead ECG data is commonly recorded using a low-pass filter with a cutoff frequency of 100 Hz or greater. The ability of the SA to quantify changes in the ventricular depolarization and repolarization sequence make the SA potentially attractive in a number of different 12-lead ECG monitoring applications. However, the 12-lead ECG data is obtained in such monitoring applications is typically recorded using a low-pass filter cutoff frequency of 40 Hz. The aim of this research was to quantify the differences between the SA computed using 100 Hz low-pass filtered ECG data (SA100) and the SA computed using 40 Hz low-pass filtered ECG data (SA40). We quantified the difference between the SA100 and the SA40 using a study population of 726 subjects. The differences between the SA100 and the SA40 were quantified as systematic error (mean difference) and random error (span of Bland-Altman 95% limits of agreement). The systematic error between the SA100 and the SA40 was found to be 0.13° [95% confidence interval: 0.10° to 0.15°]. The random error was quantified as 0.97° [95% confidence interval: 0.47° to 1.49°]. The findings of this research suggest that it is possible to accurately determine the value of the SA when using 40 Hz low-pass filtered ECG data. This finding indicates that it is possible to record the SA in monitoring applications where 40 Hz low-pass filtering is common.
S31: Monday, 12 September, 2016
11:45
S31
Chairs: Marek Malik and Luca Mainardi
Artificial Rhythm Recognition using Portable Cardiomonitor and Mobile Application
Maria Chaykovskaya*, Alexander Kalinichenko, Ekaterina Fetisova, Sergey Mironovich and Alexey Kiprensky
Patients with implanted pacemakers (PM) are usually not familiar with their pacing modes and other device settings. Modern bipolar endocardial pacing leads with close proximity of cathode and anode produce such a small pac-ing artifact that often could not be separated from noise. It becomes a chal-lenge to judge about the underlying rhythm and current pacing mode using single ECG tracing. Good stimuli artifacts visualization and understanding of its interaction with QRS plays crucial role in ECG. In case of broad complex arrhythmias, PM dependent patients and patients with resynchronization system, stimuli artifacts and QRS shape are useful for differentiation normal paced rhythm from ventricular arrhythmias and PM malfunctions. The novel portable cardiomonitor includes removable iPhone (5/5S) case with built-in electrodes and an application with original algorithm. ECG was recorded between hands, and equals to I lead of standard 12-lead ECG. Cardiomonitor uses high sensitivity capacitive electrodes and original algo-rithm of stimuli artifact detection. All recordings were made in patients during hospitalization due to device (re-) implantation or follow up visits. The whole spectrum of cardiac pacing devices from different manufactures was tested: PMs (n=37), implantable cardioverter-defibrillators (n=34) and cardiac re-synchronization systems (n=16). In 85 consistent patients, we made 100 re-cordings using different pacing modes: DDD (n=66), VVI (n=11), biventricu-lar pacing (n=17), AAI (n=6). Using novel cardiomonitor paced rhythm was identified in 100% of recordings by too independent experts. Recognition of modes switch (93%), loss of capture (84%) was also high. Definition of fusion and pseudo fusion beats was absolute (100%). Interpretation of pacing mode, made by an ex-perts 100% correlates to initially programmed ones. Single lead ECG recording with well-visualized stimuli artifacts al-lows a doctor properly to define intrinsic rhythm and all events, recorded by cardiomonitor.
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S31: Monday, 12 September, 2016
11:45
S31
Chairs: Marek Malik and Luca Mainardi
Optimisation of Electrode Placement for New Ambulatory ECG Monitoring Devices
Alan Kennedy*, Dewar Finlay, Daniel Guldenring, Raymond Bond, James McLaughlin and Keiran Moran
New single-lead ECG devices can provide continuous monitoring of cardiac rhythm for extending periods of time (72 hours – 2 weeks). A challenge of these devices is the accurate detection of the waveform features in the presence of high signal noise. In this study we aim to determine the optimal bipolar electrode placement for maximising the R-wave amplitude. The study data consisted of 117-lead body surface potential maps (BSPMs) recorded from 229 normal subjects. The dataset was randomly divided into a training dataset (172 subjects) and a testing dataset (57 subjects). A lead selection method was applied to each subject of the training dataset and a median BSPM created. The optimal bipolar ECG lead (R-lead) was then determined as the location of the absolute minimum and absolute maximum values on the median BSPM. This new bipolar lead was then compared to all leads of the Mason-Likar 12-lead ECG. The optimal placement of electrodes for recording of the R-wave are the fourth left intercostal space adjacent to the sternum and the 5th left intercostal space on the left anterior axillary line. These positions also correspond to the location of the precordial electrodes associated with V2 and V5 of the 12-lead ECG. The R-lead showed significant improvement in median R-wave amplitude over the next best lead, Mason-Likar lead II (2493.65µV vs. 1579.60µV, Wilcoxon sign ranked test, p<0.001). The R-lead can provide an improvement in signal amplitude of the R-wave. This modified electrode position may lead to more accurate identification of R-waves in the presence of high signal noise and as such can lead to more accurate cardiac rhythm monitoring.
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S32: Monday, 12 September, 2016
11:45
S32
Chairs: Raymond Bond and Thomas Hilbel
Old Dog, New Tricks - In Silico Characterization of Antazoline Cardiac Safety
Sebastian Polak*, Bartosz Lisowski, Bogna Badyra, Roman Piotrowski, Piotr Kulakowski, Joanna Giebultowicz, Piotr Wroczynski and Barbara Wisniowska
Antazoline is a first generation antihistaminic drug with high efficiency in termination of atrial fibrillation (72% vs 10% placebo). However, the mechanism of antiarrhythmic activity of antazoline and its impact on the ion channels in myocardium are unknown. Unlike quinidine it has fewer side effects, and may be free of the problem of "sudden cardiac death" attributed to quinidine. The aim of this preliminary study was to investigate the effect of antazoline on human left ventricle electrophysiology as an element of its safety profile assessment. Input data included free plasma concentration measured at 11-time points after intravenous injection of antazoline mesylate (100 mg) to 10 healthy volunteers. Four scenarios were investigated for various concentration dependent (expressed as IC50) ionic currents inhibition values: IKr (PatchClamp measured = 3.34 µM or QSAR predicted = 6.07 µM) alone or in combination with QSAR predicted IKs = 0.19 µM, INa = 21.07 µM, and ICaL = 369.5 µM. TNNP04 model implemented in Cardiac Safety Simulator (CSS) was utilized to run the simulation at the population level including physiological (volume of cardiomyocytes and sarcoplasmic reticulum) and circadian variability (plasma ions concentration and heart rate). Heterogeneous 1D string of cells (Epi, Mid, Endo) were utilized and pseudoECG was analysed for QT and QRS intervals values and their antazoline concentration dependence. Study was blinded in a way that simulations were run prior to the clinical ECG readings, and compared afterwards. Regardless of the tested scenario there was no significant concentration – QTcF correlation. For scenarios including four main ionic currents maximum QTcF value reached 511 ms (1 individual > 500 ms), which suggests that QSAR predicted IKs inhibition was overestimated. The results are also in good agreement with the observed values (max QTcF = 495 ms), and shows potential use of in silico models for drugs characterization.
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S32: Monday, 12 September, 2016
11:45
S32
Chairs: Raymond Bond and Thomas Hilbel
An Eye-Tracking Assessment of Coronary Care Nurses during the Interpretation of Patient Monitoring Scenarios
Jonathan Currie, Raymond R. Bond*, Paul McCullagh, Pauline Black, Dewar D. Finlay and Aaron Peace
Introduction: Given patient monitoring is a crucial duty, nurses need to be optimally trained regarding the interpretation of vital signs at the bedside. Training solutions and policies have been introduced to improve patient monitoring but issues such as alarm fatigue, incorrect readings and sub-optimal decision making still exist. The visual attention of a nurse when reading a vital signs monitor has yet to be determined and analysed for whether it can identify levels of competency. Eye-tracking has been used in healthcare research (e.g. for surgery, document reading, situational awareness) and has provided insight into cognitive processes. Methods: An eye-tracking study was designed to capture the visual attention of nurses when verbally interpreting five different monitoring scenarios using text vignettes and simulated vital signs as displayed on a monitor. Assessment (competency) was scored 0-10 and with each given a grade of low (0-5), medium (6-7) or high (8-10). Recording of delta heart rate (DHR) and NASA-TLX was used to assess effort and cognitive workload. Audio was recorded to capture interpretation and their stated confidence (1-10, 10=confident). 11 coronary nurses (mean experience: 8.73±5.09 years) were recruited. 55 observations collected. 101 eye tracking metrics (ETMs) were used in the analysis. Results: Mean score = 6.64±1.37 with mean confidence = 7.15±1.2. Mean NASA-TLX score = 254.55±55.25 (42.4±9.2%) for cognitive workload and DHR of -3.9±22.33bps. Mean duration for all scenarios (TotalDur) = 440.45±66.81s. Whilst no ‘strong’ correlations were found between score and any individual ETM, DHR, NASA-TLX, confidence or TotalDur, a selection of ETMs were statistically significant (p<0.05) in correlating with score (Table 1). Conclusion: Even small eye-tracking studies such as this one (n=55 observations) can show statistically significant correlations between some ETMs (n=7) and the level of competency (score). Further work could discover the full extent of ETMs for discriminating between novices and experts.
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S32: Monday, 12 September, 2016
11:45
S32
Chairs: Raymond Bond and Thomas Hilbel
Estimating Fetal Gestational Age Using Cardiac Valve Intervals
Faezeh Marzbanrad*, Ahsan Habib Khandoker, Yoshitaka Kimura, Marimuthu Palaniswami and Gari Clifford
Estimation of the gestational age (GA) is crucial for antenatal diagnosis, monitoring fetal growth, predicting the delivery date and management of pre- and post-term pregnancies. The established gold standard involves obstetric ultrasound measurements to estimate Crown-Rump Length, which provides accurate GA estimation but is affected by genetic variations, inherent variability of growth, unsuitable positioning of the fetus and operator error. High equipment cost, lack of skilled sonographers or physicians also limit the use of ultrasound in low income countries. Various Fetal Heart Rate Variability (FHRV) parameters have been used as affordable and less specialized alternatives for estimating the GA. FHRV patterns can also be used to assess the development of the fetal brain. However, FHRV patterns are influenced by arrhythmias, fetal behavioral states, heart rate patterns and maternal conditions. In this paper a novel automated method is proposed to estimate the gestational age based on the intervals between fetal cardiac valve timings and the Q-wave of fetal electrocardiogram (fECG). The intervals were estimated automatically from one-dimensional Doppler Ultrasound and noninvasive fECG. Among the intervals, Electromechanical Delay Time (the interval between Q-wave and mitral closing), Isovolumic Contraction Time (the interval between mitral closing and aorta opening), Ventricular Filling Time (the interval between mitral opening and closing) and their interactions were selected in a stepwise regression process. Compared with Crown-Rump Length as gold standard, a mean absolute error of 3.8 weeks was obtained using leave-one-out cross validation. This method also outperformed a FHRV-based approach which resulted in mean absolute error of 5.1 weeks. Since valve intervals reflect the autonomic function, the proposed method provides a novel measure of the fetal autonomic nervous system development that may be growth curve independent. As a result the proposed method might also provide indications of IUGR early in pregnancy and potentially lead to early interventions.
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S33: Monday, 12 September, 2016
11:45
S33
Chairs: Maria de la Salud Guillém and Olaf Doessel
ECG Imaging of Focal Atrial Excitation: Evaluation in a Realistic Simulation Setup
Danila Potyagaylo, Axel Loewe and Olaf Dössel*
Introduction: Recently, the ECG imaging field experienced great attention from both clinical and engineering communities. One very promising potential application is noninvasive reconstruction of atrial activities. However, despite numerous clinical studies, which are mostly concerned with complex irregular excitation patters, there are relatively few in silico investigations on the imaging of ectopic activations. In the present work, we explore the localization accuracy of ECG imaging of atrial focal sites. Methods: For the forward calculations, we used 4 realistic geometrical models with complex anatomical structure and a rule-based fiber orientation embedded into the atrial model. Excitation propagation was simulated with the monodomain model. For each geometrical model, 8 activation sequences were simulated: 4 foci were situated near the superior vena cava and thereby corresponded to variability in the sinus node location. Furthermore, 4 pulmonary vein (PV) foci – two from left and right PVs respectively – were considered. Based on the bidomain theory, the body surface potential maps resulting from these focal events were computed. For the inverse reconstructions, we employed a full-search procedure based on the fastest route algorithm (FRA). Results: The FRA-based method delivers the whole heart correlation coefficients (CC) maps together with the computed best solution. In all considered reconstructions, the location of a true focus was situated within the regions of highest correlation. Conclusion: In this study, we examined the performance of the rule-based FRA method in localization of atrial foci simulated with highly realistic anatomical and electrophysiological models. The analysis demonstrated the ability of CC maps to correctly image the areas of high probability for atrial foci locations.
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S33: Monday, 12 September, 2016
11:45
S33
Chairs: Maria de la Salud Guillém and Olaf Doessel
Evaluation of Combined Noninvasive Electrocardiographic Imaging and Phase Mapping approach for Atrial Fibrillation: A Simulation Study
Remi Dubois*, Ali Pashaei, Josselin Duchateau and Ed Vigmond
Background: Recent developments in body surface mapping and computer processing have allowed non-invasive mapping of atrial activation during cardiac arrhythmias with increasingly finer resolution. We developed a “non-invasive atrial fibrillation (AF) mapping workflow” that combines Electrocardiographic Imaging (ECGi) and phase mapping to localize reentry and focal areas during ongoing AF. However, it remains challenging to determine the accuracy of this approach because data for validation is inaccessible in humans and animal models. The aim of this study was to use simulated data to quantitatively evaluate the methodology. Methods: We used a computed tomography (CT)-derived bilayer computer model of the atria, which incorporated structural and conductive elements, including left and right atria, discrete connection paths between them, fiber orientation, pectinate muscles, and inflow vessels. A modified Courtemanche human atrial ionic model was used. We ran the first simulation (Sim1) on a structurally normal model, inducing reentry by an ectopic focus centered around a pulmonary vein after a normal beat originating from the sinoatrial node. A second simulation (Sim2) was run on a ‘diseased’ model in which fibrotic tissue was introduced by stochastic element removal based on Late Gadolinium Enhancement Magnetic Resonance (LGEMR) data of AF patients. The extracellular potentials on the epicardium were computed and propagated homogeneously to the surface using a Boundary Element Method. The body surface potentials obtained were spatially sampled in 252 locations to replicate clinical settings. The “non-invasive AF mapping workflow” was applied to body surface data to reconstruct the potentials and the phase signals on the epicardial surface of the heart. Phase signals, phase singularity locations, and local AF cycle length were compared to those computed directly from the transmenbrane potentials. Results: The AF cycle lengths were well estimated for the two sets of data (mean magnitude of relative errors MRE=5.4% and 3.8% for Sim1 and Sim2 resp.). These results were stable when adding up to 10 dB of noise on the body surface electrodes or 7.5+/-3.4mm error on electrode locations (5.6%,and 3.9%). The phase locking value (PLV) were respectively 0.62 and 0.78, indicating a fair correlation between the phase signals. Regions showing reentries were well localized with phase singularities that were stable according to electrical and geometrical noise. Conclusion: The spatial distribution of the AF cycle length and the location of the phase singularities are useful features to target ablation. We showed in this work that they can be estimated using a combine approach of ECGi and phase mapping.
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S33: Monday, 12 September, 2016
11:45
S33
Chairs: Maria de la Salud Guillém and Olaf Doessel
High Frequency Driving Sites Anchor to Fibrotic Regions in Chronic Atrial Fibrillation
Nathan Angel, Derek Dosdall, Rob MacLeod and Ravi Ranjan*
Introduction: Atrial fibrosis is linked to atrial fibrillation (AF). We used a chronic animal model of AF to test the hypothesis that fibrosis anchors sites of high frequency activation during AF, which may drive the arrhythmia. Methods: Endocardial electrical recording were measured from a constellation catheter placed in the left atrium (LA) of chronic AF dogs (n=6) (AF > 12 months). A geometric shell, created using an electro-anatomical mapping system was then fused with a LA wall created by segmenting a T1 MRI. Regions of the lowest 10% T1, were used as a surrogate measure of fibrosis. Electrograms with high frequency activations were determined through dominant frequency (DFs) analysis during AF. The highest 10% DF values for each minute of AF were placed in a spatial map of probability during the 30 min AF episode and were compared with regions of fibrosis. Results: The AF animals had at least one site of high DF which was stable for at least 22.5 (75 %) of 30 minutes of AF and these sites were within 1.4±1.2 mm of T1 determined fibrosis. Stable high DF sites occurred more significantly within 2 mm of fibrosis than in other regions of the atrium (p<0.05, chi square). The mean DF was 8.5±1.2 Hz and the highest DF sites showed an average DF of 10.3±1.1 Hz. In 5/6 chronic AF animals, regions of high DF bordered regions of structural remodeling as determined by T1 MRI. Discussion: Heterogeneous atrial remolding, specifically the development of fibrosis, arising from chronic AF may provide a substrate that anchors sites of high DF. Cardiac T1 Mapping MRI provides a means to determine such fibrotic sites noninvasively and ablating these sites reduced the stability of AF.
S33: Monday, 12 September, 2016
11:45
S33
Chairs: Maria de la Salud Guillém and Olaf Doessel
Noninvasive Identification of Atrial Fibrillation Drivers: Simulation and Patient Data Evaluation
Maria de la Salud Guillem Sánchez*, Andreu M Climent, Miguel Rodrigo, Ismael Hernández-Romero, Alejandro Liberos, Francisco Fernández-Avilés, Omer Berenfeld and Felipe Atienza
Background Identification of atrial drivers as singularity points by using the inverse problem of electrocardiography is being used to guide atrial fibrillation (AF) ablation. However, the ability of the inverse problem to reconstruct fibrillation patterns and identify AF drivers has not been validated. Methods Position of AF drivers was compared between recorded and inverse computed EGMs by making use of (1) realistic mathematical models and (2) simultaneous endocardial and body surface recordings during AF ablation procedures. Specifically, 30 different AF episodes with different degrees of complexity were simulated with realistic atrial and torso anatomies. In addition, for two patients with chronic AF, endocardial (128 recording points distributed in both atria) were recorded together with torso surface recordings (57 leads). Inverse problem of electrocardiography was computed by applying 0-order Tikhonov regularization. Atrial drivers were defined as the areas with the highest dominant frequencies (HDF) or at the sites with a higher incidence of long-lasting phase singularities (PS). Results On simulation data, HDF analysis allowed the correct identification of the chamber that harbored the AF source in 30 out of 30 of the models evaluated vs. 26 out of 30 models for PS analysis. On patient data, the highest incidence of PS was inscribed inside the highest DF area for the actual EGMs recorded by the multipolar catheter baskets. Solution of the inverse problem only allowed identifying atrial drivers on the correct atrial chamber by HDF analysis (2 out of 2 patients vs. 0 out of 2 patients for PS analysis). Conclusion Identification of atrial sources by solving the inverse problem of the electrocardiography is more reliably accomplished in the frequency domain than based on PS detection. Alternative methods for inverse problem resolution to zero-order Tikhonov regularization may be required for their application in AF.
S34: Monday, 12 September, 2016
11:45
S34
Chairs: Cristiana Corsi and Yi Su
Automatic Segmentation of Mitral Leaflet Movement in Doppler Tissue M-Mode Ultrasound
Kasper Sørensen*, Samuel Emil Schmidt, Peter L Sørensen, Anne-Sofie Korsager, Jacob Melgaard, Peter Søgaard and Johannes Struijk
Introduction: Doppler Tissue M-Mode ultrasound facilitates a method for measuring both mitral and aortic valve opening and closing. These measures can be used when assessing global information about the cardiac cycle. The method depends on an operator to manually setting points in the ultrasound image to obtain the timing intervals. We developed an automatic segmentation algorithm that segmented the mitral leaflet movement line, to guide the clinician in this work. Methods: The algorithm used a series of steps to reduce noise in the image, leaving only the region of interest left with the mitral leaflet movement line. Next the gradient of the image was calculated with a the Sobel method, creating a high gradient on the edge of the mitral leaflet movement line. Using a multidimensional weight matrix the mitral leaflet movement was tracked in the image. The automatic algorithm is validated against three human operators. Results: In 19 of 29 images the correlation coefficients are larger then 0.8 between the algorithm and the mean of the operators. The median operator standard deviation within the 95% CI was 5 pixels. The median rms error for the algorithm was 4 pixels. Conclusion: The novel method of automated segmentation the mitral leaflet movement line has a high accuracy but depends on the quality of the image.
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S34: Monday, 12 September, 2016
11:45
S34
Chairs: Cristiana Corsi and Yi Su
Respiratory Motion Correction for 2D Cine Cardiac MR Images using Probabilistic Edge Maps
Ozan Oktay, Giacomo Tarroni*, Wenjia Bai, Antonio de Marvao, Declan O'Regan, Stuart Cook and Daniel Rueckert
Background. Short axis (SA) cine MR images are of crucial importance for the accurate assessment of cardiac anatomy and function. SA cine stacks are routinely acquired during multiple breath-holds: different breath-hold positions can have detrimental effects on a variety of clinically relevant tasks (e.g. volumetric estimation). In this study, we proposed a novel approach to spatially align motion corrupted SA slices in MR image stacks using 3D probabilistic edge maps (PEMs) generated with structured decision forests. Methods. PEMs are learning-based image representations outlining the contours of a specific object of interest (the myocardium, in this case). Through training, structured decision forests are able to associate to each 2D SA image (slice i of the stack) 3D PEMs representing the contours for slices i and i+1. The overlap between 3D PEMs generated from adjacent slices allows to correct the in-plane spatial misalignment using a block matching registration algorithm. This approach was tested on SA cine stacks acquired from 26 healthy subjects for whom anatomical 3D (A3D) cardiac images were also available as reference. A 3D multi-atlas segmentation technique was applied to estimate end-diastolic left ventricular volumes respectively from the A3D images (EDVref), the 2D SA image stacks before (EDVpre) and after slice-alignment using the proposed approach (EDVpost-PEMs) and using a conventional intensity-based registration method (EDVpost-I). Inter-slice alignment was assessed measuring differences between EDVref values and EDVpre, EDVpost-PEMs and EDVpost-I values, respectively. Results. Volume differences between EDVpost-PEMs and EDVref (7.73±6.55 ml) were smaller compared to differences between EDVpre and EDVref (10.34±9.41 ml) and EDVpost-I and EDVref (10.76±9.64 ml). The improvement in volume estimation was observed to be statistically significant (p = 0.01). Conclusion. The experimental results show that volumetric measurements on 2D cine cardiac MR stacks can be improved by using the proposed respiratory motion correction method.
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S34: Monday, 12 September, 2016
11:45
S34
Chairs: Cristiana Corsi and Yi Su
A Miniaturized MEMS Motion Processing System for Nuclear Medicine Imaging Applications
Mojtaba Jafari Tadi*, Eero Lehtonen, Jarmo Teuho, Antti Saraste, Mikko Pänkäälä, Mika Teräs and Tero Koivisto
Background. In cardiac and oncologic Positron Emission Tomography (PET) imaging, cardiac and respiratory motions may impair the image quality and the quantitative accuracy of the heart imaging. To reduce motion-related inaccuracies, cardiac and respiratory gating methods are the most common approaches applied in clinical PET imaging. Methods. We used tri-axial micro-electromechanical (MEMS) accelerometer and gyroscope sensors attached to the test subjects’ chest to extract seismocardiographic (SCG) and gyrocardiographic (GCG) motion signals. Our main objective was to assess the capability of MEMS motion sensor -based measurements in improving the dual gating technique. The main hypothesis for this work was that mechanical sensors could be used improve the quality of detection and estimation of the quiescent periods in cardiac respiratory cycles. Concurrent 10 minute recordings of MEMS-based SCG and GCG, electrocardiography (ECG), and Real-time Position Management (RPM) were performed, processed and analysed using healthy volunteers as test subjects. Results. Signal processing algorithms for extracting PET gating information from cardiac and respiration signals were developed. The cardiac cycles detected with the MEMS-based SCG and GCG measurements are highly correlated with the reference ECG cycles in terms of interval durations (RSCGvs.ECG = 0.999, RGCGvs.ECG = 0.998). Mechanical signals are also able to accurately indicate the timings of systolic and diastolic phases suitable for cardiac gating, as compared to the ECG. Moreover, gyroscope and accelerometer derived respiratory (GDR and ADR) motion signals are found to have high linear correlation with the reference RPM (RGDRvs.RPM= 0.998, RADRvs.RPM= 0.997). Conclusion. The proposed MEMS motion sensor -based gating, and the developed algorithms, may potentially improve the accuracy of nuclear medicine imaging specifically in cardiac and oncologic PET images. These promising first results warrant for further investigations, and the application of the developed methods on PET imaging data.
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S41: Tuesday, 13 September, 2016
08:30
S41
Chairs: Johan De Bie and Matthias Gorges
Closing the Data Loop: An Integrated Open Access Analysis Platform for the MIMIC Database
Mohammad Adibuzzaman*, Ken Musselman, Alistair Johnson, Paul Brown, Zachary Pitluk Pitluk and Ananth Grama
Recent advances in computational sciences have brought major changes in many fields such as image processing and computational biology. However, that change has not been translated to clinical application to its potential. Primary obstacles include lack of communication between data scientists and clinicians, technical difficulties due to the heterogeneous data and lack of understanding of the risk and benefit resulting in the absence of regulatory guideline. One major initiative for large data collection in clinical setting is MIMIC III, created and maintained by the Laboratory for Computational Physiology at MIT. It has two main components, ‘clinical’ and ‘waveform’. With the current access platform, it is difficult for a researcher to use the database without extensive knowledge of programming language and different database architectures. For any research initiative with this database, many steps are recurrent to each research project; e.g., i) high level exploration of the database, ii) integration of heterogeneous data sources, iii) cohort selection according to clinical criteria, and iv) use of different algorithms. Consequently, researchers use significant resources to reinvent the wheel for each research project which acts as a major barrier for translational clinical research with this publicly available dataset. To address this issue, we have designed and developed a software tool that would enable the researchers to integrate disparate data sources, automatic cohort selection and use different well known algorithms. The architecture uses an array database, ‘SciDB’ with distributed computing for the ‘waveform’ and structured query language ‘PostgreSQL’ for the ‘clinical’ database. The ‘R’ software platform is used for the integration. The demonstration of this open source software tool would show the ease and flexibility of using the tool for terabytes of data for different research problems. The software architecture would help expedite clinical research to address the gaps between large data collection and translational impact.
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S41: Tuesday, 13 September, 2016
08:30
S41
Chairs: Johan De Bie and Matthias Gorges
Telecardiology under Resource Constraint: Low-complexity Compact Representation of ECG
Roopak Tamboli and Soumya Jana*
Aim: Compact, yet faithful, representation of ECG signals to meet bandwidth and power constraints remains central to successful telecardiology in infrastructure-deficient areas. Towards practical realization, we seek desired compactness in the class of low-complexity transform representations. Key Idea: A typical ECG signal consists of a strong rhythmic (low-pass) component, with compact Fourier transform (FT) representation, and temporally localized (high-pass) features, efficiently represented by wavelet transform (WT). Accordingly, we propose a compact representation consisting of suitable Fourier and wavelet coefficients. As computation of such coefficients is at most O(n log(n)), our representation inherits the desired low complexity. Method: We considered 43 annotated ECG records of the MIT-BIH Arrhythmia database. From those, overlapping signal vectors of length 256 samples, each containing an R-peak, were formed. We then optimized the pair (K1, K2), where K1 Fourier coefficients and K2 wavelet (Daubechies-4, `db4') coefficients respectively represent the rhythmic component and localized features, and jointly achieve a target fidelity. The number, K1+K2, of coefficients in our method was compared to that required to achieve the same target fidelity using (i) WT (`db4'), (ii) discrete cosine transform (DCT), and (iii) FT. Results: Compared to DCT, FT and WT representations, respectively, the proposed method used 51%, 30% and 11% less number of coefficients on the average at a target fidelity R^2=98%. Indeed, the figure shows the superiority of our method for most individual records. Our result assumes practical significance as improved efficiency was achieved without sacrificing low complexity. Here, note that Karhunen Loeve transform (KLT) provides the best compaction, albeit, at a higher complexity.
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S41: Tuesday, 13 September, 2016
08:30
S41
Chairs: Johan De Bie and Matthias Gorges
Design of an Electronic Upload and Reporting System aimed at Corelab Tasks and Responsibilities in Multi-center Clinical Trials
Jan Walter Benjamins*, Yoran M. Hummel, Jan Peter Busman, Frans Riepma, Bernard Dorhout and Joost P. van Melle
Echocardiography plays a substantial and ever growing role in cardiovascular clinical trials. In large scale multicenter clinical trials these images are interpreted and analyzed by an imaging core laboratory (ICL) to generate consistent results with the least possible variance. Currently, transfer of the images can be achieved in 2 ways; via postal services (physical media) or web-based via upload portals that merely act as a digital substitute for traditional logistics. We describe the design of a new software system that facilitates general ICL logistics, such as digital transfer of images, automated DICOM data verification, semi-automated image quality assessment, reporting and database generation in multicenter clinical trials. It fully integrates with most commonly used medical systems and contributes to cost efficiency aspects of running multicenter trials. The system was built in .NET, implementing modern web standards, HL7 and DICOM healthcare communication standards. Web security principles were applied to the developed components and the deployed application configuration. The system consists of two major subsystems, first being an internet application that serves as an upload portal for sites and as a report tool for clinical research organizations (CRO’s). The second component is an intranet application which is accessible through the local network. Both components have access to a shared database and file-share, where images are stored by the internet application and pushed forward to the medical system by the intranet application. After images have been interpreted by ICL-personnel, the analysis results are reported back to the ICL system, that sends automated notifications to CRO’s with relevant updates about the specific trial. All steps in the workflow are guided by and validated against the trial design. Validation failure(s) at any point are reported instantaneously to all persons concerned with the specific event, consequently increasing efficiency and possibly reducing trial costs.
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S41: Tuesday, 13 September, 2016
08:30
S41
Chairs: Johan De Bie and Matthias Gorges
Machine Learning Approaches for Supporting Patient-Specific Cardiac Rehabilitation Programs
Danilo Lofaro*, Maria Carmela Groccia, Rosita Guido, Domenico Conforti, Sergio Caroleo and Gionata Fragomeni
Cardiac rehabilitation is typically recommended for the follow up management of cardiovascular diseases. Physical training prevents the recurrence of cardiovascular events, and increases life expectancy, lowering cardiovascular morbidity and mortality risk. Previous studies investigated the application of Machine Learning approaches for the prediction of the rehabilitation outcome in terms of physical performance as well as of the length of stay after acute cardiovascular events, but fewer reports are focused on using predictive models to support clinicians in the choice of a patient-specific rehabilitative treatment path. In this work, we analysed data relative to two years activity of a rehabilitation clinic in South Italy to derive a prediction model for supporting clinicians in the planning of personalized rehabilitation programs. We collected data concerning 129 patients admitted for cardiac rehabilitation after a major cardiovascular event, relative to: anthropometric measures, surgical procedure and complications, comorbidities and physical performance scales at admission. The prediction outcome was the rehabilitation program divided in four different paths. Algorithms used to find the best predictive model were tailored implementations of Lasso Regression, Linear/Polynomial/Radial SVM, Random Forest, Bagged Flexible Discriminant Analysis, C5.0 and Bagged CART. Models performance were measured by prediction accuracy. Parameters tuning has been optimized basing of performance on a 5-fold cross-validation. R 3.2 and caret package 6.0 were used for analyses. Mean model accuracy was 0.748 (SD 0.0165). Best model selected was polynomial SVM with parameters degree = 3, scale = 0.01 and C = 2, showing a global classification accuracy of 0.769. Five most important variables for prediction were cardiac risk class, six minutes walking test, borg scale, age, MRC dyspnea scale and FEV1/FVC ratio at rehabilitation initiation. Machine Learning techniques have shown to be a reliable tool for support clinicians in the decision of cardiac rehabilitation treatment path.
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S41: Tuesday, 13 September, 2016
08:30
S41
Chairs: Johan De Bie and Matthias Gorges
An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead Electrocardiogram Interpretations
Andrew Cairns*, Raymond Bond, Dewar Finlay and Daniel Guldenring
The 12-lead Electrocardiogram (ECG) is ubiquitously used as a diagnostic support tool to detect cardiovascular disease. However, it is difficult to read and is often incorrectly interpreted due to the significant cognitive load forced upon the interpreter. To help alleviate this cognitive workload and to decrease diagnostic time, this format of ECG presentation is often supplemented with computer analysis, which routinely presents the interpreter with an automatically generated ECG interpretation. That being said, computerised analysis of an ECG is often inaccurate as machine algorithms struggle to recognise patterns and shapes in noisy ECG signals. Therefore, it is recognised that computerised ECG interpretation should always be over-read by a clinician. However, since current computerised ECG interpretation often only provides a single diagnosis, it can contribute to a number of cognitive biases. To combat these concerns, a decision support algorithm has been developed to provide multiple potential ECG diagnoses. As part of a de-biasing strategy multiple possible interpretations are presented to encourage differential diagnosis. This study augments an interactive sequential approach to ECG interpretation (IPI model) with a semi-automatic rule-based algorithm to suggest multiple potential diagnoses. To accomplish this, the rule-based algorithm assesses an interpreter's response to each question in the IPI model. The algorithm is semi-automatic and is based on annotations inputted by the human interpreter. Therefore, this is an optimal man-machine model for ECG interpretation as a human observer is better at recognising patterns and shapes in noisy signals whilst a machine is better at reasoning based on a large set of rules. Therefore, we hypothesise that the algorithm may have greater accuracy compared to conventional computer ECG diagnostics which focus on signals that are often noisy and difficult to process. The algorithm was implemented using web technologies and uses the independent storage format JSON to define the rules
S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
Impact of Three Dimensional Atrial Fibrosis on Development and Stability of Rotational Activity in Atrial Fibrillation – A 3D Simulation and Clinical High-density Mapping Study in Peristent Atrial Fibrillation
Markus Rottmann*, Ufuk Aslan, Wenzel Kaltenbacher, Viktor Markstein, Thomas Arentz, Olaf Dössel and Amir Jadidi
Introduction: The arrhythmogenic mechanisms of AF are still not understood. Increased atrial fibrosis is a structural hallmark in patients with persistent AF. Methods: We assessed the electrogram signature rotational activity and their spatial relationship to low voltage areas (increased fibrosis) in patients with persistent AF. Computer simulations implicating 3-dimensional atrial tissue with different amount of atrial fibrosis were used to assess development and stability of rotational activities (rotors) during AF. Results: A series of computer simulations with 3-D atrial fibrosis (40% de-gree) implemented in an area of 10mmx10mmx2mm was carried out. Rotor anchoring occurred at the borderzone between fibrosis and healthy atrial tissue with 12 consecutive rotations prior to rotor extinction. Rotational activity in fibrotic tissue resulted in fractionated signals and were overlapped with large negative electrograms in unipolar recording mode from neighbouring healthy tissue – impressing as a focal source. Conclusion: Necessary conditions for development and stability of rotational activities around fibrosis were on the one hand a minimum size of atrial fibrosis area equal or larger than 10mm x 10mm and on the other hand a degree of atrial fibrosis of 40%. Clinical data showed that AF termination sites were located within low voltage areas (displaying <0,5mV in AF on the multi-electrode mapping catheter) in 80% and at their borderzones in 20% of cases.
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S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
The Effect of Conductivity Values on Activation Times and Defibrillation Thresholds
Barbara Johnston*, Josef Barnes and Peter Johnston
Aims: Uncertainty in the input parameters used in simulation studies needs to be taken into account when evaluating the results produced by such studies. This work considers the effect of using various sets of bidomain conductivity values in simulations of activation times and defibrillation thresholds in a realistic whole heart model. Methods: Activation time maps indicating the propagation of the depolarisation wavefront through the cardiac tissue are generated using two types of sets of bidomain conductivity values: four-conductivity datasets (where normal and transverse conductivities are assumed equal) and six-conductivity datasets, including newly proposed sets that are based on experimental measurements. These maps are produced by solving the bidomain model, along with an individual cell model of the electric current, on a mesh of a canine heart. In addition, simulations are carried out in a 'heart in a bath' model, where a shock is delivered from two opposing patch electrodes. Defibrillation thresholds that indicate the minimum potential difference that is required to defibrillate the heart are determined for the above sets of conductivities. Results: The activation time maps show significant differences depending on the conductivity set used, as do the defibrillation thresholds. The defibrillation thresholds vary by more than 20%, whereas the activation times for epicardial breakthrough and total depolarisation both vary by approximately 50%. It is found that the most extreme values in each case are produced by two of the four-conductivity datasets. Conclusions: Significant differences in activation time maps and defibrillation thresholds are found, depending on the conductivity set that is used for the simulation. Since these differences are sufficiently large that they may lead to different conclusions in such studies, it is suggested that the four-conductivity datasets may not be an appropriate choice for use in simulation studies in the heart.
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S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
Biventricular Pacing Optimization by Means of the Dyssynchrony Parameter
Pavel Jurak*, Pavel Leinveber, Josef Halamek, Filip Plesinger, Tereza Postranecka, Jolana Lipoldova and Miroslav Novak
Introduction: Cardiac Resynchronization Therapy (CRT) represents an effective treatment for ventricular dyssynchrony. Biventricular pacing synchronizes delayed left ventricle lateral wall (LV) activation with the septum and right ventricle wall (RV). A positive response is manifested by shortening of the QRS and increase of the LV ejection fraction. To improve the CRT effect, different interventricular delay (VV) settings can be used to optimize resynchronization. Here we test two different VV delay settings: 0 ms. – simultaneous LV and RV activation, and 20 ms LV pre-activation. Methods: 12-lead 5 kHz ECG during 5-minute resting supine position was measured in 47 patients with CRT OFF and CRT ON with VV delay 0 (CRT_0) and -20 ms (CRT_20). The atrioventricular delay was minimized to suppress any spontaneous conduction. We detected QRS duration (QRSd) and computed the dyssynchrony parameter DYS as the time difference between center of gravity of 500-1000 Hz averaged envelopes in the V1 and V6 leads in the QRS complex region (see Fig, bottom panel). Results: 32 of 47 patients (68 %) had a positive CRT_0 response manifested by QRSd shortening of 33.2±20.9 ms and DYS decrease of 51.9±30.9 ms. 28 of 32 patients (87 %) had a positive LV pre-excitation effect: QRSd additional shortening of 4.7±5.9 ms and DYS decrease of 12.6±7.5 ms. The correlation coefficient of QRSd and DYS changes (CRT_0 vs CRT_20) was 0.23 and indicates the information diversity. Conclusion: both the QRSd and DYS parameters during LV pre-excitation manifest significant decrease (p < 0.001). The DYS parameter differs from QRSd and provides significantly higher response to VV delay change (p < 0.001). There is potential for the use of the DYS parameter as an additional predictive value for improved CRT VV delay selection.
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S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
Can Continuous Models Capture Details of Reentry in Fibrotic Myocardium?
Tanmay Gokhale*, Eli Medvescek and Craig Henriquez
Motivation: Cardiac arrhythmias have traditionally been simulated using continuous models that assume tissue homogeneity and use a relatively large spatial discretization. However, it is unclear how well the continuous model is able to accurately capture the discrete effects of fibrosis that may be implicated in arrhythmogenesis. The objective of this study was to build microstructural discrete models of fibrosis and compare behavior with conduction velocity-matched continuous models. Methods: Two dimensional models of anisotropic cardiac monolayers (6mm x 3mm) that incorporate discrete cells with uniformly distributed gap junctions were randomly generated. 70% of lateral gap junctions were decoupled to replicate adult tissue connectivity. Collagen septa of variable length (mean = 300 micron) were inserted, parallel to cardiac fiber orientation, to disrupt between 0% and 30% of the remaining transverse coupling between myocytes. The Bondarenko membrane model of the mouse ventricular myocyte was used. Conduction was simulated in each tissue, and an equivalent continuous model was created, with longitudinal and transverse conductivities selected to match the longitudinal and transverse conduction velocities of the microstructural model. Spiral waves were then induced in each tissue mode via cross-stimulation, and the cycle length and tip trajectory were recorded. Key Results: 20% fibrosis lead to a 45% slowing in transverse conduction. At 0% fibrosis, the spiral wave behavior of the microstructural model was closely matched by the continuous model (cycle length 67 msec vs 64 msec). However, at 20% fibrosis, the cycle length was substantially longer in the microstructural model than the continuous model (92 msec vs 72 msec), due to a longer reentry pathway because of the pattern of fibrosis in the tissue. Conclusion: These results suggest that continuous models adapted to simulate fibrotic tissue may still fail to capture key details of reentry caused by the discrete nature of fibrosis-induced heterogeneity.
S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
The Strength-Interval Curve for Blood Vessels
Adam Connolly* and Martin Bishop
Wavefronts from virtual-electrodes, in response to field-stimulation, are thought to be the main mechanism behind the success of low-energy defibrillation protocols. In this work the concept of the strength-interval curve, usually associated with uni-polar stimulation, is extended to field-stimulation for specific geometrical features - in this case blood-vessels (with realistic fibre architecture and lumen structure) - as the coronary vasculature is known to be an important source of virtual-electrode induced wavefronts, in response to field-stimuli. Using the bidomain model for myocardium, we observed break-excitations in response to low-strength field stimuli, at early diastolic intervals - while the surrounding tissue was relatively refractory. Break-excitations were only possible due to the relative proximity of regions of de and hyper-polarization around the vessel, and the associated strength-interval curves (for sufficiently large vessels) displayed a reduction in shock-strength for early diastolic intervals - an effect known from the literature on uni-polar stimulation. This leads us to conclude that it may be possible to optimize low-energy defibrillation shock protocols to take advantage of this effect, in order to minimize the total energy used and maximize the probability of successful defibrillation.
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S42: Tuesday, 13 September, 2016
08:30
S42
Chairs: Martin Bishop and Gunnar Seeman
Regularity of Node Distribution Impacts Conduction Velocities in Finite Element Simulations of the Heart
Eike Moritz Wülfers, Olaf Dössel and Gunnar Seemann*
Cardiac excitation propagation simulations on complex geometries benefit from flexible tetrahedral meshes. These meshes can contain elements of different sizes. Unfortunately, simulated conduction velocity (CV) seems to not be independent from mesh element sizes as shown in a monodomain N-version benchmark of the cardiac modeling community. Use of the consistent (vs. lumped) mass matrix as well as ionic current integration techniques have previously been identified as influencing this mesh-dependency. This work shows that regularity of node distribution in meshes contributes strongly as well. Although the existence of effects caused by regular node distributions is known for other applications of the finite element method (FEM), they have not previously been studied in cardiac electrophysiology simulations. Excitation propagation was simulated using a FEM discretization of the monodomain equation. Operator splitting was used to separate integration of the partial differential equation and ionic current calculations. The resulting linear algebra problem was solved with the PETSc framework. Simulations were conducted on tetrahedral meshes of a cuboid (dimensions 3mm x 7mm x 20mm). At different spatial resolutions h, meshes of regularly arrayed nodes (Delta{x,y,z}=h) were created. Corresponding meshes with less regular node distributions were generated using a 3-d Delaunay triangulation (Gmsh algorithm, with mean and standard deviation of element edge length matching the regular meshes). After stimulation at one corner, resulting simulated activation times (ATs) of the node in the diagonally opposite corner were evaluated. Using the consistent mass matrix and h=0.1mm, ATs of 40.11ms and 39.72ms were recorded for the regular and irregular mesh, respectively. ATs increased with increasing h, but at h=0.7mm the AT observed on the regular mesh was 80.01ms already, whereas only 47.52ms were recorded for the irregular mesh.
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S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
The Pressure Gradient across the Endocardium
rachad shoucri*
Based on the theory of large elastic deformation of the myocardium, a mathematical relation for the pressure-volume relation (PVR) in the left ven-tricle was derived, in which the active pressure of the myocardium (also called isovolumic pressure Piso by physiologists) is included in the mathematical formalism describing the PVR. Also a mathematical expression for the non-linear end-systolic pressure-volume relation (ESPVR) was derived, from which an expression of the pressure gradient (Piiosm – Pm) /Pm across the inner surface of the myocardium (endocardium) was obtained (Pisom = peak isovolumic pressure when the myocardium reaches its maxi-mum state of activation, Pm = corresponding left ventricular pressure). In the figure we compare the calculated ratio of pressures Pisom / Pm to the ejection fraction EF (stroke volume / end-diastolic volume) and to the ratio of areas SW/TW (stroke work / total area under the ESPVR), for a group of normal patients (*) and a group of patients with aortic stenosis (o). The figure shows that the three indexes give consistent results. In particular we see that the group of aortic stenosis can be subdivided into three subgroups, one subgroup (three cases) corresponds to normal values for EF and SW/TW, a second subgroup (seven cases) has increased values for Pisom / Pm and reduced values of SW/TW with respect to the normal group, and a third subgroup (two cases) has reduced values of Pisom / Pm and increased values of SW / TW with respect to the normal group. In the second subgroup, an increase in Pisom corresponds to an increase in TW and a decrease in Pm corresponds to a decrease in SW (˜ Pm*stroke volume), resulting in a decrease of SW/TW. In the third subgroup a decrease in Pisom corresponds to a decrease in TW and an increase in Pm corresponds to an increase in SW, resulting in an increase in SW/TW.
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S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
Estimation of End-Diastolic Pressure via Deconvolution
Christoph Hoog Antink*, Daniel Rüschen, Steffen Leonhardt and Marian Walter
Left ventricular assist devices (LVADs) can significantly improve survival rate and quality of life for patients suffering from end-stage heart failure. Several promising strategies to control LVADs are being developed, some being focused on the end-diastolic pressure (EDP). For those, the problem of EDP estimation in real-time has to be solved. In this work, a generally applicable deconvolution-based method to identify features in cardiac signals is presented. This method is applied to the estimation of the EDP from the left-ventricular pressure (LVP) signal and evaluated on animal trial data. In 11 trials with adult sheep, a myocardial infarction was induced and an LVAD was implanted. A total of 37.6 hours of LVP data, corresponding to 201885 ED time points, was annotated by a medical expert. Using these annotations, a desired signal that highlights the end-diastolic (ED) time point is created. Next, linear FIR filter coefficients are estimated that transform the LVP signal into an estimation of the desired signal. To evaluate the concept, the filter coefficients estimated in one trial are used to estimate the desired signal in the remaining 10 trials. In this forward operation, convolution of the LVP signal with a linear FIR filter is performed, which is computational inexpensive and introduces a delay of only 36 ms. Next, a basic peak detection strategy is applied to locate the ED time point. Using this form of cross validation, an average root mean square error of 11.6 ms / 4.1 mmHg was achieved. This demonstrates the potential of the presented deconvolution method for feature extraction and processing of cardiac signals. With a robust, real-time capable method for EDP detection at hand, it is possible to implement closed-loop LVAD control strategies that restore physiological left ventricular filling pressures.
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S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
Diastolic Augmentation Index Improves Augmentation Index in Assessing Arterial Stiffness
Yang Yao, Lisheng Xu*, Yu Wang, Yahui Zhang, Yingxian Sun and Liang Guo
Arterial stiffness is an important risk factor for cardiovascular (CV) events and is increasingly used in clinical practice. Radial augmentation index (AI) is used in assessing arterial stiffness, but is not only dependent on pulse wave velocity (PWV), but also on several other factors like the reflect distance of the pulse wave and height. This paper improved radial AI in assessing arterial stiffness by d-value (the subtraction between radial AI and dAI). Twenty-one subjects aged 22 to 80 years (mean±SD, 44±22 years) were enrolled in this study. The PWV, AI and dAI of each subject were measured. The d-value (r=0.81, P<0.0001) shows better linearity with PWV than AI (r=0.76, P<0.0001) and dAI (r=-0.72, P<0.005) do. In conclusion, dAI improves AI in assessing arterial stiffness.
S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
Exploratory Study of the Cardiac Dynamic Trajectory in the Embedding Space
Jorge Oliveira*, Bruna Cardoso and Miguel Coimbra
In this paper, the topological and dynamical properties of the heart sounds are assessed. The signal is pre-processed and projected into an embedding subspace, which is more suitable to detect the irregularities and the unstable trajectories registered during the cardiac murmurs than the original heart sound signal. We present a method for heart murmur classification divided into five major steps: a) signal is divided into heart beats; b) entropy gradient envelogram is computed (per heart beat) from the pre-processed signal; c) the orbital trajectories are reconstructed using the embedding theory; d) n orbits in the embedding subspace are extracted (per heart beat); e) the median of the n orbits is used as an input to K-Nearest Neighbors (KNN) classifier. The experimental results achieved in the mitral, tricuspid pulmonic spots are in agreement with the current state of art for heart murmur classification.
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S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
Heart-valve Sounds Obtained with a Laser Doppler Vibrometer
Johannes Struijk*, Kim Munck, Bolette Dybkjær Hansen, Nina Jacobsen, Louise Pilgaard, Kasper Sørensen and Samuel Emil Schmidt
Aims: Several modalities for recording of heart sounds have been used since the late 1800s. Microphones and accelerometers have been the obvious choices since the beginning of the 20th century, showing that a wealth of information about cardiac movement is available outside the audible fre-quency range as well as about the audible valve sounds and murmurs. The present work investigates the use of a Laser Doppler Vibrometer (LDV) to record valve sounds and characterizes those recordings. Methods: An LDV (Polytec PDV-100) was used to measure the normal component of the velocity of the chest wall at 30 points (grid of 6 x 5 points) in each of seven subjects. The recorded signals were analyzed in the frequen-cy domain and bandpass filtered (20-80 Hz) to obtain the S1 and S2 heart sounds. From all grid points, a center of energy (CoE) was calculated for the signal energy, separately for the S1 and S2 sounds. Results: The LDV signal reached a noise floor for a frequency of >80 Hz, whereas 99% of the signal energy was below 80 Hz. The signal to noise ratio was approximately 24 dB if measured directly on the (caucasian) skin, and up to 45 dB if special markers were used. There was little difference in signal amplitudes between measurement points on the ribs as compared with the intercostal spaces. Amplitudes of the valve sounds were below 1 mm/s. The mean centers of energy were to the left of the sternum, with the CoE of the S2 sound about 11 mm superior to the CoE of the S1 sound on average. Conclusion: The LDV is an interesting new, non-contact, modality for the recording of heart sounds with excellent signal quality and reproducibility.
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S43: Tuesday, 13 September, 2016
08:30
S43
Chairs: Dingchang Zheng and Roberto Sassi
Computer Simulations of Three-dimensional Blood Flow in Patient-specific Aorta Models with Aortic Aneurysms
Jun-Mei Zhang*, Dian Farhana Binte Haron, Adrian Shoen Choon Seng Low, Boyang Su, Kenny Yoong Kong Sin, Ru San Tan, Hua Zou and Liang Zhong
Background and Aims: Aortic diameter is considered as the primary criterion to decide surgical repair of abdominal aorta aneurysm (AAA) and thoracic aorta aneurysm (TAA). However, it has limitations as some aneurysms rupture below size thresholds, while others grow to a large size without rupture. We hypothesize that low wall shear stress (WSS), whereas flow recirculation and thrombus deposition predominated, may be associated with the progression and rupture risk of aortic aneurysm. Methods: Two patients (subject 1 and 2) with both TAA and AAA were recruited. Standard computed tomography (CT) or magnetic resonance imaging (MRI) were performed at baseline and follow-up. Phase contrast MRI was performed to obtain the blood flow at the ascending and descending aorta positions. Patient-specific aorta models were reconstructed from the most recent MRI images and the computational domains were discretized by a total of 572,622and 781,691 cells respectively. To solve Navies-Stokes equations, time-average flow rate measured with phase-contrast MRI was assigned to the aorta inlet and resistance boundary conditions were used for all the outlets. During 3-month follow-up, TAA of subject 1 was found to grow from 6.2 cm to 7.1 cm., therefore subject 1 was elected for surgical repair of TAA. However the size of aneurysms kept stable for subject 2, who was only clinically followed-up. Results: Skewed streamlines were observed in the bulge of aneurysms for the two subjects (see planes AA, CC, DD, EE and FF in figure), wherein there were vortices and relatively low WSS. In contrast to subject 2, subject 1 had relative larger size of low WSS regions at TAA. Conclusion: The low WSS obtained from computer simulation, as a stimulus of wall degeneration, may be associated with the rapid growth of TAA in size for subject 1. Customized patient-specific simulation may facilitate the disease monitoring and treatment planning.
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S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
A Vectorcardiographic Evaluation of the Consensus Criteria for Early Repolarization
Peter L Sørensen*, Kasper Sørensen, Jacob Melgaard, Johannes J Struijk, Steen M Hansen, Jørgen K Kanters, Jonas B Nielsen, Jesper H Svendsen, Stig Haunsoe, Lars Koeber, Anders G Holst, Adrian Pietersen, Christian Torp-Pedersen, Freddy K Lippert and Claus Graff
Introduction: A 2015 consensus paper proposed a unified definition of the early repolarization (ER) pattern based upon quantification of end-QRS notches and slurs. In this study we investigated the relationship between end-QRS concave “bite” segments in the vectorcardiogram (VCG) and the ER pattern of end-QRS notches and slurs. Methods: Digital 12-lead ECG recordings were obtained from 1561 subjects. Notches and slurs were quantified according to the consensus criteria. Stipulations important to this study are that notches should be entirely above the baseline and occur on the terminal half of the downsloping R-wave. ER manifestations were divided into 3 types: A) notches only B) notch and slur C) slurs only. The 3D VCG was derived from the digital recordings using the inverse Dower transform. End-QRS bites were defined as bites with a starting point in the terminal half of the QRS loop and an end-point within the terminal quarter of the QRS loop. An automatic algorithm developed by the authors was used to quantify bites in 3D. Results: Of 1561 subjects 85 (5.4%) fulfilled the ECG consensus criteria for ER. ER types A and B were in 100% of cases associated with an end-QRS bite in the VCG, whereas type C occurred both in the presence and absence of a bite. Additionally, we observed that bites of similar duration and amplitude, due to a combination of QRS loop orientation and projection onto the 12-leads, could be associated with the following configurations in the ECG: notch, slur, notch not fully above baseline and notch occurring above the terminal half of the R-wave. Conclusion: The results of this study indicate that the ER pattern manifest as end-QRS bites in the VCG and that the orientation of the bite relative to the 12 leads determine the ECG presentation as either notching or slurring.
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S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
Ensemble Classifier Based on Linear Discriminant Analysis for Classifying Brugada Syndrome Patients According to Symptomatology
DANIEL ROMERO*, Mireia Calvo, Nathalie Béhar, Philippe Mabo and Alfredo Hernandez
Background: Brugada syndrome (BrS) is characterized by the occurrence of syncope and sudden death due to cardiac arrhythmias. To date, the only effective therapy for symptomatic BrS patients with an aborted sudden cardiac death or documented ventricular fibrillation is the placement of an implantable cardioverter–defibrillator (ICD), however, it is difficult to identify high-risk subjects requiring an ICD among asymptomatic BrS patients. Methods: A 12-lead ECG recording during a standardized exercise test was acquired for 62 patients suffering from BrS (symptomatic, n=14). For each patient, conventional HRV indices from time-frequency analysis and heart rate recovery (HRV features), as well as several morphological depolarization indices (QRS features: wave amplitudes, main QRS slopes and angles, QRS width and QRS vector magnitude) were evaluated at relevant stages of the test. The most discriminant features were selected for both the HRV and QRS features using a feature selection algorithm and applied for model classification building. For the detection step, linear discriminant analysis was used. The performance of the obtained models was assessed via k-fold cross-validation and the best features of each model were employed for building the final classification model. Results: After feature selection, the detection performance using the symptomatic group as the target class, was for each individual model as follows: HRV-based model: Se=0.93, Sp=0.98, AUC=0.97; QRS-based model: Se=1, Sp=0.71 AUC=0.91. When joining the best features of both models (HRV-QRS-based model), the classification performance increased up to Se=1, Sp=0.96, AUC=0.99. Conclusion: This study shows that using both HRV and depolarization analysis, a better risk stratification of BrS patients can be performed. The proposed method may provide a quantitative means to confirm the implantation of an ICD on symptomatic patients, to select asymptomatic BrS patients that may benefit from an ICD or to perform follow-up on BrS patients.
S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
The Role of Reduced Left Ventricular, Systolic Blood Volumes in ST Segment Potentials Overlying Diseased Tissue of the Ischemic Heart
Brett Burton*, Kedar Aras, Jess Tate, Wilson Good and Rob MacLeod
INTRODUCTION While shifts in the ST segment of the ECG are used routinely in clinical practice to detect myocardial ischemia, there remains ambiguity especially about the interpretation of ST segment depression. In this study, we focus attention on the role of changing ventricular shape and blood volume on ST segment potentials. Myocardial ischemia arises from reduced coronary blood flow, leading to ST segment changes in epicardial and body surface electrodes. To simulate ST segment depression, some computational models have incorporated reduced intracellular or elevated extracellular anisotropy ratios and/or large, thin subendocardial ischemic regions. However, most models fail to consider the effect of cardiac cycle on epicardial ST potentials, i.e. reduced intracavitary blood volume during systole. We hypothesize that reduced ventricular blood, representative of end systole, will alter the ST segment depressions in epicardial leads overlying the ischemic zone. METHODS We incorporated a thin, subendocardial ischemic zone geometry into a realistic canine ventricular model governed by the static bidomain equation. Left ventricular volume was incrementally reduced, while maintaining the size and general shape of the ischemic region, in order to reflect the systolic phase of the cardiac cycle. Epicardial potentials were subsequently assessed to determine the effects on ST-segment depression. RESULTS Using our model, we were able to confirm three previously reported scenarios that resulted in ST depression overlying the ischemic zone. However, the reduced blood volume models also showed that ST-depression magnitudes diminished, and eventually disappeared, during simulated systole. DISCUSSION Our models show that the blood volume at an end systolic state has an important impact on recorded ST depressions in overlying epicardial leads. These results suggest that the blood volume plays a key role in ST-segment shifts and also that incorporating time dependent geometries in cardiac models may be important for accurate simulation of ischemia.
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S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
Diagnosis and Prognosis of the V-index in Patients with Symptoms Suggestive of Acute Myocardial Infarction in the Emergency Departement
Roger Abächerli*, Raphael Twerenbold, Roberto Sassi, Luca Minardi and Tobias Reichlin
Introduction: The V-index is an ECG marker quantifying the spatial heterogeneity of ventricular repolarization. We prospectively investigated the diagnostic and prognostic value of the V-index in patients with symptoms suggestive of acute myocardial infarction (AMI). Methods: We enrolled 582 patients presenting with suspected AMI to the emergency department (ED) in a prospective observational study. Twelve lead ECG’s of five minutes were recorded at presentation to the ED. The V-index was calculated in a blinded fashion. Final diagnosis was adjudicated by two independent cardiologists. Patients were followed for the endpoint of all-cause mortality. Results: AMI was the final diagnosis in 16% of patients. Values for the V-index at presentation were higher in patients with AMI compared to other causes of chest pain (23ms (IQR 18-28) vs. 18ms (IQR 15-24), p<0.001). The diagnostic accuracy of the V-index at presentation for the diagnosis of AMI as quantified by the area under the receiver operating characteristic curve (AUC) was 0.64 (95% CI 0.57-0.71). The use of the V-index in addition to conventional ECG criteria improved the sensitivity of the ECG for MAI from 41% to 85% (p<0.001). Median V-index levels in deceased patients were significantly higher as compared to survivors (28ms (IQR 22-37) vs. 19ms (IQR 15-24), p<0.001). Cumulative 24-month mortality rates were 99.5%, 97.2% and 90.4% according to tertiles of the V-index (p<0.001). In multivariable Cox proportional hazard analysis, the V-index significantly predicted mortality independently of age and high-sensitive cardiac Troponin T (hs cTnT). Conclusion: The V-index, an ECG marker quantifying the spatial heterogeneity of ventricular repolarization, significantly improves the sensitivity of the ECG for the diagnosis of AMI and predicts mortality in patients with suspected AMI independently of age and hs-cTnT.
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S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
Prevalence of Ventricular Ectopy in Older Adults across Different Frailty Levels
Saman Parvaneh*, Bijan Najafi, Nima Toosizadeh, Irbaz Bin Riaz and Jane Mohler
Background: An increased prevalence of ventricular ectopy (Premature Ventricular Contraction, PVC) is associated with increased incidence of congestive heart failure (CHF) and increased mortality. Previous studies demonstrated that incidence of ventricular ectopy increases with age, but to the best of our knowledge its association with frailty, a geriatric syndrome that is associated with adverse health outcomes, has not been studied. The aim of this study was to study the prevalence of PVC in older adults across different frailty levels. Method: A wearable ECG recorder was used to record four hours of uni-channel ECG in 45 older adults aged 65 and above. Participants were classified as non-frail (n=21), pre-frail (n=18), and frail (n=6) using the well-validated Fried Frailty phenotype. Matlab was employed to identify PVCs, and the subsequently manually reviewed by an expert to ensure accuracy. Number of PVC beats per hour was considered for ECG assessment and Analysis of variance (ANOVA) test was used to evaluate the extracted parameter among frailty groups. Statistical level of significance was set to p= 0.05. Results: Number of PVC beats was not significantly different (p>0.05) between non-frail (43.74±69.22), pre-frail (48.24±74.48), and frail (22.12±7.83). The average number of PVC beats was higher in pre-frail compared to non-frail. Interestingly, the average number of PVC beats was 52% and 54% less in frail population compared to non-frail and pre-frail Discussion: In this study, no association between prevalence of PVC and frailty level was found. The higher variation in prevalence of PVCs for non-frail and pre-frail may be related to the diversity of participants in these two groups.
S44: Tuesday, 13 September, 2016
08:30
S44
Chairs: Elaine Clark and John Wang
A Multi-Stage decision support Algorithm to Rule-Out patients with suspected Acute Myocardial Infarction (AMI)
Cesar Oswaldo Navarro Paredes*, James A Shand, Mary Jo Kurth, David J McEneaney and James McLaughlin
Objective: Provide a multi-stage rule-out algorithm to stratify patients admitted to the Emergency Room (ER) with chest pain of presumed ischemic origin. The aim is to keep at-risk patients in the ER providing a proper care while minimizing overcrowding. The algorithm uses data from biomarkers —heart-type fatty acid–binding protein (H-FABP), high sensitivity cardiac troponin T (hs-cTnT) measured at different times (presentation, 1, 2, 3, 6, 12 and 24 hours) together with ECG at presentation. Methods: Data in a randomly selected training set of 296 patients were retrospectively analysed. 182 cases comprised a test set. STEMI were not considered since biomarkers are not routinely measured for these cases. H-FABP and hs-cTnT were statistically significant for the segregation of non-MI cases over other biomarkers including CK-MB and cTnT. The multi-stage algorithm was trained and tuned looking for maximizing sensitivity (and keeping low numbers of false negative cases in the detection of AMI). Thus after each stage if the algorithm detects non-MI, the patient could be considered for release. Results: Retrospectively applying the algorithm on the whole dataset of 478 cases: 97 MI (NSTEMI) and 381 non-MI. 244 patients could have been recommended for rule-out at presentation with 3 false negatives which in turn could have been identified by other symptoms/history. Sensitivity: 0.97, specificity: 0.63, ppv: 0.40, npv: 0.99. The remaining patients would have needed to be observed and biomarkers measured again at 1 hour were the next stage algorithm would rule-out patients from AMI. The process is repeated to the following stages and the algorithms exhibit high sensitivities (0.94 at 3 hours) with moderately increasing specificity (0.80 at 3 hours). Conclusion: The algorithm serves as a rule-out test for suspected AMI patients which would allow risk stratification and a more efficient use of resources to the health care system.
S51: Tuesday, 13 September, 2016
10:30
S51
Chairs: Peter Johnston and Stef Zeemering
A New Model of the Human Atrial Myocyte with Variable T-tubule Organization for the Study of Atrial Fibrillation
Michael A Colman*, Niall Macquaide and Antony Workman
Introduction: Atrial fibrillation (AF) is characterized by an inability of the atria to contract in a coordinated and regular fashion, underlain by rapid and irregular electrical activity. AF can promote strokes through blood clots, and may also predispose to ventricular arrhythmias. As the most common sustained cardiac arrhythmia, AF is a significant drain on healthcare re-sources. Atrial myocytes have been shown to have variable densities and organization of transverse-tubules (TTs), and this may play a role in pro-arrhythmic calcium handling. However, currently available models of human atrial single cell electrophysiology do not account for this property. In this study, we developed a new model human atrial electrophysiology and spatio-temporal, stochastic calcium handling which accounts for various configurations of TT organization and density. Methods: A model of 3D spatio-temporal calcium handling was developed for the human atria, in a similar manner to previous ventricular models. This was then coupled with a newly developed ionic model, fit primarily to single-lab data to ensure self-consistency. A mixed deterministic (ionic model) and monte-carlo (calcium handling) simulation approach was implemented. Calcium release units (CRUs) were then assigned to either contain a TT (with inclusion of L-type calcium channels and the sodium calcium exchanger) or be a ‘naked dyad’ (without inclusion of membrane ion currents). TT geometry is based on our own imaging data of TTs in multiple human atrial cells. Results: In control conditions, the model reproduces behavior observed experimentally. TT organization had a significant influence on spatio-temporal calcium cycling, promoting gradients in the intracellular space and calcium store. Spontaneous calcium waves often originated from localized regions of CRUs with no TTs due to these gradients. Conclusion: We have developed a novel model of the human atria for the investigation of the influence of TTs on sub-cellular calcium activity and the development of AF.
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S51: Tuesday, 13 September, 2016
10:30
S51
Chairs: Peter Johnston and Stef Zeemering
Personalized Modeling Pipeline for Left Atrial Electromechanics
Thomas E Fastl*, Catalina Tobon-Gomez, William A Crozier, John Whitaker, Ronak Rajani, Karen P McCarthy, Damian Sanchez-Quintana, Siew Y Ho, Mark D O'Neill, Gernot Plank, Martin J Bishop and Steven A Niederer
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by uncoordinated atrial activation with consequent deterioration of mechanical function. Personalized computational modeling provides a novel framework for integrating and interpreting the combined role of atrial electrophysiology and mechanics in AF development and sustenance. High-resolution coronary computed tomography angiography data were acquired and retrospective analysis was conducted on three patients. Statistics-based image segmentation was performed via isolation of the left atrial blood cavity and identification of the left atrial myocardium utilizing personalized image thresholds followed by standardized mitral valve extraction and pulmonary vein shortening. The smoothed voxel representations were discretized into tetrahedral finite element (FE) meshes using an Octree-based mesh generator for unstructured meshing. To estimate the complex left atrial fiber architecture, the endo- and epicardial surfaces were registered onto an atrial atlas containing distinct landmarks, subsequently projected onto the personalized geometry defining specific left atrial regions. Individual fiber fields were generated according to clinical guidance on both surfaces for constituting regions based on local solutions of Laplace's equation and transmurally interpolated to all tetrahedral elements. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity and high-resolution tetrahedral FE meshes. The novel algorithm for automated incorporation of the left atrial fiber architecture provided realistic estimates of the atrial microstructure and was able to qualitatively capture all important fiber bundles. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts and facilitates simulations of atrial electromechanics. This allows the comparison between healthy controls and AF patients to quantitatively investigate the causative link between atrial electrophysiology and mechanics to identify the capacity of the atria to sustain AF.
S51: Tuesday, 13 September, 2016
10:30
S51
Chairs: Peter Johnston and Stef Zeemering
Predicting Spiral Wave Stability by Personalized Electrophysiology Models
Cesare Corrado*, John Whitaker, Henry Chubb, Steven Williams, Matt Wright, Jaswinder Gill, Mark O'Neill and Steven Niederer
Introduction: Identifying atrial tissue that is capable of supporting sustained re-entrant spiral wave activation patterns offers a potential ablation target for atrial arrhythmias. Currently this substrate can only be characterized during fibrillation and requires a large and expensive specialized multi electrode catheter. We propose a novel method to personalize biophysical ionic models from multi-electrode catheter measurements and to predict the spiral wave stability using computer simulations. Methods: Personalized biophysical model of cellular electrophysiology (EP) was fitted to local conduction velocity (CV) and effective refractory period (ERP) restitutions measured using an s1-s2 pacing protocol applied at the central poles of a decapolar catheter. A two dimensional 5 x 5 cm2 homogeneous atrial wall EP model was created using the personalized EP model. A cross-field stimulation was then applied to trigger a spiral wave within the model and the spiral tip path was tracked to quantify spiral wave stability. Results: CV and ERP were measured for 5 cases with paroxysmal AF undergoing pulmonary vein isolation and ionic model fitted. Spiral wave stability in each case was predicted using tissue simulations, identifying distinct stable (2/5), meandering and breaking up (2/5) and unstable self terminating (1/5) spiral tip patterns for different cases. Conclusion: We have developed and applied a novel technique for predicting local tissue substrate using conventional diagnostic catheters and pacing protocols.
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S51: Tuesday, 13 September, 2016
10:30
S51
Chairs: Peter Johnston and Stef Zeemering
High Resolution Microscopic Optical Mapping of Anatomical and Functional Reentries in Human Cardiac Cell Cultures
Andreu M Climent*, Ismael Hernández-Romero, Maria de la Salud Guillem Sánchez, Nuria Montserrat, Maria Eugenia Fernández, Felipe Atienza and Francisco Fernández-Avilés
Introduction: Limited knowledge of the mechanisms of perpetuation of fibrillation is hampering the development of effective anti-arrhythmic treatments. The goal of the present study is to present a novel technology to map with high resolution (500x500um) the center of fibrillation drivers in order to characterize the mechanisms of reentry. Methods: Cell cultures of human cardiomyocytes differentiated from pluripotent stem cells were analyzed with a novel microscopic optical mapping system. Calcium imaging was developed by recording emission light of Fura 2-(AM) (Ca2+ sensitive probe, TEFLabs, Inc, Austin, TX. USA). During fibrillation the dominant driver was identified (i.e. anatomical vs. functional reentry) and characterized in terms of its dominant frequency (DF). The pharmacological response to verapamil administration of each type of reentry was analyzed. Results: In all analyzed cell cultures, a reentry was identified as the mechanism of maintenance of the arrhythmia. Microscopic analysis of the reentries allowed their classification into (1) micro-anatomical (46%, N=12) or functional reentries (54%, N=14). Isochronal maps of a representative example of each group are shown in the figure. Anatomical reentries presented lower DFs than functional reentries (i.e. 1.08±0.19 vs. 2.96±0.24Hz, p<0.01). Interestingly, the administration of verapamil produced opposite effects in each group: whereas DF increased in 15±3.4% for anatomical reentries, it decreased in 11.9±6.8% for functional rotors (p<0.01). Conclusions: Microscopic optical mapping of reentries allows the identification of perpetuation mechanisms which has been demonstrated to be linked with different pharmacological response.
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S51: Tuesday, 13 September, 2016
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S51
Chairs: Peter Johnston and Stef Zeemering
Epicardial Fibrosis Explains Increased Transmural Conduction in a Computer Model of Atrial Fibrillation
Ali Gharaviri*, Mark Potse, Sander Verheule, Rolf Krause, Angelo Auricchio and Ulrich Schotten
Introduction: Recent work has shown that the transition from persistent to permanent AF in goats coincides with an increase in fibrosis in the outer millimeter of the atrial wall. Macroscopically this leads to reduced electrical conductivity orthogonal to the dominant fiber orientation. A causal relation has not been established yet. Our purpose was to test if epicardial fibrosis can explain the increased incidence of transmural conduction (breakthroughs), which is also observed in permanent AF. Methods: We constructed a detailed geometry of the human atria including epicardial layer and all major endocardial bundle structures. The model also includes realistic one to three layers of fiber orientations, corresponding to their location in the atrium. Computer simulations were run with a mesh of 0.2 mm resolution and Courtemanche human atrial cell model. Epicardial fibrosis was modeled by assigning zero transverse conductivity to a random selection of model elements in the epicardial layer. Simulations were performed with 0, 50, and 70% affected elements. Results The numbers of waves, phase singularities, and breakthroughs (BTs) were quantified at different degrees of fibrotic tissue. Increase in the “fibrotic” volume from zero (Control) to moderate (50% Fibrotic), and severe (70% Fibrotic) increased both the number of waves and the number of phase singularities. Along with the increase in fibrosis, the endo-epicardial electrical activity dyssynchrony increased from 8.6% to 18.6%, and 38.4%. Fibrosis increased the incidence of BTs. Conclusion: This model is the first anatomical atrial model to display BTs, a common and conspicuous feature in experimental studies on AF. Epicardial fibrosis in this model increases the degree of endo-epicardial electrical activity dyssynchrony and the incidence of BTs, thus increasing the complexity of fibrillatory conduction. The model offers the opportunity to study transmural conduction, which frequently occurs during AF, in more detail.
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S51: Tuesday, 13 September, 2016
10:30
S51
Chairs: Peter Johnston and Stef Zeemering
Dynamic Behavior of Rotors during Human Persistent Atrial Fibrillation as observed using Non-Contact Mapping
Nawshin Dastagir*, Tiago Almeida, Xin Li, Frederique J Vanheusden, Gavin S Chu, Peter J Stafford, G Andre Ng and Fernando S Schlindwein
Rotors have been related to atrial fibrillation (AF) maintenance. We analyzed the behavior of rotors in persistent AF (persAF) utilizing a novel non-contact methodology and compared this to real time dominant frequency (DF) analysis. 2048 noncontact virtual unipolar atrial electrograms (AEGs) were collected simultaneously (EnSite Array, St.Jude Medical) from 10 persAF patients (duration: 34±25months) undergoing left atrial (LA) ablation. After QRST-removal, FFT was used to identify the global DF of the LA (range 4-10Hz; 1s time-window; 50% overlap; highest-DF (HDF) (DF-0.25Hz); up to 20s/patient). The frequency organization of AEGs was measured by the organization index (OI). Phase was found via Hilbert-transform. Phase singularities (PSs) and their chirality were identified and tracked. The PSs were categorized according to their lifespan into short (lifespan <80ms) and long-lived (rotors) (lifespan =80ms) (Fig-1A). A total of 6261 PSs were tracked. 5.2% (IQR: 0.44~5.7%) of the tracked PSs were long-lived (Fig-1A) and were observed in 20% (IQR: 2.5~35%) of the windows. The numbers of PSs observed at any instant are shown in Fig-1B, demonstrating that 60% of the time no PSs were observed. Furthermore, up to 13 PSs were also observed at any time instant and complex clustering of PSs were seen. Fig-1C illustrates complex PSs clustering for one patient during 1.5s. The window with rotors showed significantly higher HDF (mean±SD, 8.0±0.43Hz vs 7.71±0.53Hz, p<0.0001) and lower OI (0.76±0.04 vs 0.79±0.03, p<0.0001) when compared with the short-lived PSs window (Fig-1D). During persAF, the LA showed distinct behaviors as characterized by rotors. Often, no rotors were observed during sustained AF and, when present, the rotors continually switched between organized and disorganized behaviors. Long-lived rotors correlated with higher atrial rates. From these data we conclude that rotors are not the sole perpetuating mechanism in persAF and that dynamic DF analysis can identify sites of long-lasting rotor activity.
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S52: Tuesday, 13 September, 2016
10:30
S52
Chairs: Ronald Wilders and Vincent Jacquemet
An Algorithm for Fitting Local Membrane Parameters to an Action Potential Duration Map in a Tissue with Electrotonic Interactions
Angelina Drahi, Akshay Kota Aswath Kumar and Vincent Jacquemet*
Repolarization gradients contribute to arrhythmogenicity. They can be introduced in computer models of cardiac tissue by locally adjusting an intrinsic parameter of the membrane model. Electronic coupling, however, modulates the dispersion of action potential duration (APD). We developed an algorithm to iteratively adjust the spatial distribution of a membrane parameter in order to reproduce a given APD map. A 3D atrial monodomain model with Courtemanche-based kinetics and anisotropic conduction was used. The adjustable local parameter was acetylcholine (ACh) concentration. Random patches with a length scale of 2 cm were distributed over the atria. After rescaling and Gaussian smoothing with different widths, synthetic target APD maps covering the range 105 to 135 ms with maximal gradients of 5, 10, 20 and 30 ms/cm were created. APD was computed at a threshold of -70 mV during normal propagation. The problem was first solved in the absence of coupling using spline interpolation of the APD vs ACh curve obtained in an isolated cell. Further refinements of the solution in the coupled tissue were calculated using Newton iterations in which the Jacobian was approximated in the low coupling limit. Each iteration involved a simulation in the atrial model to compute the APD map, compare it to the target APD map, and update the ACh profile. Iterations stopped when the 99th percentile of the error was < 1 ms. After the initial estimate, the error ranged from 3 to 13 ms. In all cases, convergence was reached after fewer than 10 iterations, except for the steepest gradient where the existence of an exact solution was uncertain. Convergence was faster when the maximal gradient was less steep and when coupling was reduced. This algorithm provides a tool to automatically generate arrhythmogenic substrates with controllable repolarization gradients and possibly incorporate experimental APD maps into computer models.
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S52: Tuesday, 13 September, 2016
10:30
S52
Chairs: Ronald Wilders and Vincent Jacquemet
Simulation Study on Balance of Glycolytic ATP Production and Oxidative Phosphorylation in Embryonic and Adult Ventricular Cells
Hitomi Sano*, Yasuhiro Naito and Masaru Tomita
The developmental program of the heart requires accurate regulation to ensure continuous circulation and simultaneous cardiac morphogenesis because any functional abnormalities may progress to congenital heart malformation. Energy metabolism in fetal ventricular cells is regulated differently from that in adult ventricular cells: fetal cardiomyocytes generally have immature mitochondria, and fetal ventricular cells show greater dependence on glycolytic ATP production. Here, we integrated various characteristics of fetal ventricular cells based on a mathematical model and predicted the contribution of each characteristic to maintenance of intracellular ATP concentration and sarcomere contraction under anoxic conditions. Our simulation results showed that higher glycogen content, higher hexokinase activity, and lower creatine concentration helped prolong the time that contraction of ventricular cells was maintained under anoxic conditions. The integrated model enabled us to quantitatively address the contributions of factors related to energy metabolism in ventricular cells. Because fetal cardiomyocytes show similar energy metabolic profiles to stem cell-derived cardiomyocytes and cardiomyocytes in the failing heart, an improved understanding of fetal cardiomyocytes will contribute to understanding processes in stem cell-derived cardiomyocytes and cardiomyocytes under pathological conditions.
S52: Tuesday, 13 September, 2016
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S52
Chairs: Ronald Wilders and Vincent Jacquemet
Na+ Current in Human Atrial Myofibroblasts Alters Myocyte Excitability: A Computational Study
Heqing Zhan*, Jialun Lin, Xiaoling Li and Jingtao Zhang
Aims: During pathological challenges such as cardiac fibrosis, fibroblasts proliferate and differentiate into myofibroblasts. This differentiation is accompanied by the expression of Nav 1.5 a subunit which may generate a persistent Na+ current in myofibroblasts (INa_myofb) and result in regenerative action potentials (APs) in myocytes and myofibroblasts. The goal of this preliminary study was to identify the role of INa_myofb integrated in electrotonic myofibroblast-myocyte (myofb-m) coupling on the excitability and repolarization of myocyte and myofibroblast. Methods: Mathematical modeling was done using a combination of (1) the Maleckar et al. model of the human atrial myocyte, (2) the MacCannell et al. “active” model of the human cardiac myofibroblast, and (3) our formulation of INa_myofb based upon experimental findings from Chatelier et al. For myofb-m coupling scheme, different ratios of myocytes to myofibroblasts and values of intercellular resistance were set based on available physiological data. Numerically, all state variables in electrophysiological equations were updated by means of the forward Euler method. Results: The simulation results showed that (1) for myocytes, myofb-m coupling reduced the peak of AP (Vmax), shortened the action potential duration (APD) and depolarized the resting membrane potential (Vrest) whether or not INa_myofb was involved in myofibroblasts. However, the addition of INa_myofb decreased the reductions of Vmax and APD, and increased the degree of Vrest depolarization as compared to no INa_myofb integrated in myofb-m coupling. (2) for myofibroblasts, more significant electrotonic depolarizations were exhibited with addition of INa_myofb. Conclusion: The identified effects demonstrated that INa_myofb significantly influenced myocytes and myofibroblasts properties. It should be considered in future pathological cardiac mathematical modeling, such as atrial fibrillation and cardiac fibrosis.
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S52: Tuesday, 13 September, 2016
10:30
S52
Chairs: Ronald Wilders and Vincent Jacquemet
Effects of the Transient Outward Potassium Current on Action Potential Upstroke Velocities Tested Using the Dynamic Clamp Technique
Arie Verkerk, Christiaan Veerman, Jan Zegers and Ronald Wilders*
The voltage-gated transient outward potassium current (Ito1) plays a prominent role in the early repolarization phase of the cardiac action potential (AP) and thereby contributes to the refractory period and inotropic state of the myocardium. The current is largely responsible for differences in AP repolarization between species, between left and right ventricle, and transmurally, and it is affected by various pathophysiological conditions, such as heart failure. Ito1 already activates during depolarization to potentials near –50 to -30 mV, suggesting that Ito1 may be active during the AP upstroke, but whether it modulates the maximal AP upstroke velocity ((dV/dt)max) is unknown. In the present study, we addressed this issue using the dynamic clamp configuration of the patch-clamp technique. Recordings of upstrokes were made (at physiological temperature using an alternating voltage/current clamp protocol) from HEK-293 cells transfected with SCN5A, encoding the alpha-subunit of the cardiac fast sodium current and thus responsible for the rapid cardiac AP upstroke. Ito,f of the Bondarenko et al. mouse ventricular AP model (corresponding to Ito1) was computed in a real-time simulation and injected into the real cell during its upstroke. In control conditions, i.e., without Ito,f, (dV/dt)max was 272±25 V/s (mean±SEM, n=11). With the standard settings of the Bondarenko et al. model,(dV/dt)max was unaffected by in silico Ito,f. This Ito,f, however, is based on experimental data obtained at room temperature in the presence of CdCl2. An increased activation rate of Ito,f, thereby representing a more close-to-physiological temperature, results in a small, but significant, decrease in (dV/dt)max. In addition, negative shifts in voltage-dependency of Ito,f activation, thereby balancing the non-physiological CdCl2-induced positive shift, result in a more pronounced decrease in (dV/dt)max. We conclude that Ito1 may modulate (dV/dt)max, but only when its activation is fast and its activation threshold is near -50 to -40 mV.
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S52: Tuesday, 13 September, 2016
10:30
S52
Chairs: Ronald Wilders and Vincent Jacquemet
A New Tool for the Action Potential Repolarization Dynamic Analysis: Application to the Discrimination of Diabetic and Control Cells
Olivier Meste*, Marianna Meo, Sergio Signore and Marcello Rota
Aims: In CinC2015 we have shown that the dynamics of the action potential (AP) repolarization could be tracked throughout the stimulation course. Despite some valuable outcomes, the populations of interest (control, Ctrl, and streptozotocin-induced, STZ, diabetic mice) could not be significantly distinguished in term of dynamics because of the global extracted feature. In this study, the computation of new features for each repolarization percentage allows an accurate and meaningful characterization of the two groups leading to a significant classification. Methods: APs in isolated left ventricular cardiomyocytes obtained from 41 Ctrl and 76 STZ mice were measured by patch-clamp. The progressive changes in AP repolarization for individual cells were tested on a set of 100 consecutive excitations at 2Hz pacing rate. The corresponding repolarizations are stacked in a matrix decomposed with a new approach. Observations are modeled as a sum of vectors multiplied by specific polynomial functions. This approach is similar to the SVD, but the corresponding scalars are replaced by these functions. Model unknowns are estimated by using an Alternated Least Square algorithm. Finally, the mean of the polynomial first derivative is computed for each repolarization percentage as a representative feature. Results: In our case each matrix is represented by one vector and several multiplicative polynomial functions. A Wilcoxon signed rank test (p<0.05) has been applied on the features from the two groups. We can observe a significant difference in the late repolarization phase (70%-95% repolarization), with a singular behavior in correspondence with the AP profile shoulder onset (80%). Conclusion: A new matrix decomposition adapted to the observed data has been successfully proposed to quantify the AP repolarization dynamics. The assumption that the discriminative information is hidden in the polynomials but not simply in the raw data is proven to be valid.
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S52: Tuesday, 13 September, 2016
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S52
Chairs: Ronald Wilders and Vincent Jacquemet
Numerical Analysis of Conduction of the Action Potential Across the Purkinje Fibre-Ventricular Muscle Junction
Jue Li*, Henggui Zhang and Mark Boyett
Normally, there is little conduction delay (<0.2 ms) between cells in the heart. However, at the Purkinje fibre-ventricular muscle junction (PVJ), long conduction delays (5-20 ms) are reported. The PVJ therefore has special conduction properties. In support of this, transitional cells are reported at the PVJ. A 1D model was developed consisting of a string of 49 Purkinje cells, connected to 1 transitional cell, connected to one or more strings of 40 ventricular myocytes (a Purkinje fibre is expected to activate a block of ventricular muscle). Rabbit Purkinje and left ventricular action potential models were used; the Purkinje model was also used for the transitional cell. The 1D mono-domain model was used to solve conduction. The diffusion coefficient (D) was set to 0.6 and 0.12 mm2/ms for the Purkinje fibre and ventricular muscle to give expected conduction velocities. The effects of (i) the diffusion coefficients between the terminal Purkinje cell and the transitional cell (D1) and between the transitional cell and the first ventricular myocyte (D2) and (ii) the ‘load’ on the Purkinje fibre (i.e. number of strings of ventricular myocytes) were investigated. The greater D1 (up to ~0.4 mm2/ms), the larger the load that could be supported, although further increase in D1 resulted in little further increase. Also the greater D2 (up to ~0.04 mm2/ms), the larger the load that could be supported, but in this case a further increase in D2 resulted in a decrease in the load that could be supported. The delay in conduction at the PVJ was dependent on D1, D2 and the load and increased markedly at the smallest values of D1 and D2 and the highest loads. At a certain point, a small change could lead to large increase in the delay or even conduction failure.
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S53: Tuesday, 13 September, 2016
10:30
S53
Chairs: Dewar Finlay and Frans Riepma
Difference in Pulse Arrival Time at Forehead and at Finger as a Surrogate of Pulse Transit Time
Jesus Lazaro*, Raquel Bailón, Pablo Laguna, Vaidotas Mazoras, Andrius Rapalis and Eduardo Gil
Pulse transit time (PTT) difference (PTTD) to the forehead and finger dynamics are compared to pulse arrival time towards the finger (PATF) dynamics during a tilt table test. Two frequency bands, where different physiological information is expected, are analyzed: low frequency (LF) influenced by both sympathetic and parasympathetic activity, and high frequency (HF) influenced by parasympathetic activity. As PATF, PTTD is influenced by PTT, but in contrast to PATF, PTTD is not influenced by the pre-ejection period (PEP). This is advantaging in certain applications such as arterial stiffness assessment or blood pressure estimation. Results showed higher correlation between PTTD and PATF during rest stages than during tilt stage, when the PEP dynamics have stronger effect in PATF dynamics. This suggests that PTTD variability can potentially be a surrogate of PTT variability that is not influenced by PEP, which is advantaging in the previously mentioned applications. However, further studies must be elaborated in order to evaluate the potential of PTTD in such specific applications.
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S53: Tuesday, 13 September, 2016
10:30
S53
Chairs: Dewar Finlay and Frans Riepma
Cor/log BAN BT a Wearable Battery Powered mHealth Data Logger and Telemetry Unit for Multiple Vital Sign Monitoring.
Thomas Hilbel*, Sven Feilner, Matthias Struck, Sven Hofmann, Andreas Heinig and Hugo Katus
The wireless data logger system “Cor/log® BAN BT” (CL) allows seamless 24/7 monitoring of relevant vital sign parameters. CL covers the entire period of acute point of care inside the hospital and the recovery period, when first mobility is achieved and when the patient is released into an ambulatory or homecare environment. CL is the commercial product of the German KARDIKOM telemedicine patient monitoring research project. It was the objective of the KARDIKOM project to prevent secondary life-threatening situations (myocardial infarction, heart failure, arrhythmias) for patients with cardiologic risk constellations by establishing innovative technical and organizational infrastructures for a 24/7 monitoring. Another aim of the project was to certify all components of the CL, the wireless livestream viewer and a health cloud in accordance with the European medical device directive 93/42/EEC(MDD). The CL records the relevant vital signs such as ECG, respiration, pulse oximetry with plethysmogram and movement. The vital data collected with the CL is saved on a memory card for further analysis and is simultaneously transmitted in real-time to a telemedicine server via a smartphone or tablet. The smartphone does also provide GPS position. In addition Cor/log View an Android™ Application for viewing recorded vital sign data originating from the CL was developed. CL has also a connector to the MedM health cloud. MedM is a patient data management system(PDMS) consisting of a cloud portal and a mobile health app. The MedM app runs on Android™, iOS™, Windows™ and Blackberry™. The app does setup a wireless connection to the CL and does store the vital signs in the health cloud. The MedM app and cloud is cleared as a Class I PDMS according to EU MDD. Thus CL together with its mHealth software can be used in clinical application studies for mobile vital sign recording with cloud connection.
S53: Tuesday, 13 September, 2016
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Chairs: Dewar Finlay and Frans Riepma
Atrial Fibrillation Detection Using Photo-plethysmography and Acceleration Data at the Wrist
Alberto Bonomi*, Fons Schipper, Linda Eerikainen, Jenny Margarito, Ronald Aarts, Saeed Babaeizadeh, Helma de Morree and Lukas Dekker
Background: Atrial fibrillation (AF) is a pathological condition leading to increased risk for embolic stroke and cardiac hospitalizations. Screening for AF represents a technical challenge because of the paroxysmal and frequently asymptomatic nature of the condition. Objective: The aim was to investigate whether an unobtrusive wrist-wearable device equipped with a photo-plethysmographic (PPG) and acceleration sensors could be used to detect AF. Methods: Sixteen patients (M = 63%, age: 65.2 ± 14.0 y, BMI: 29.7 ± 7.0 kg/m2) with suspected paroxysmal AF were monitored for 24 hours in outpatient setting using a portable ECG Holter recorder. Simultaneously, a wrist-wearable device equipped with a PPG and acceleration sensor was used to monitor heart rhythm and body movement. PPG data were processed to extract the timing of heart beats and derive inter-beat-intervals (IBI). Acceleration data was used to discard IBI in presence of motion artifacts. An ECG validated first-order Markov model was used to assess the probability of irregularly irregular rhythm of AF being present from PPG-derived IBI. AF detection outcome from the algorithm was compared with adjudications of AF episodes provided by clinical experts after visually inspecting ECG Holter data. Results: Four patients experienced 100% AF burden, while 1 patient suffered from atrial flutter. The remaining patients showed normal sinus rhythm with several premature beats (808 supraventricular, range 0 – 4879; and 656 ventricular premature beats, range 0 – 4795). AF detection was achieved with 97 ± 2% Sensitivity and 99 ± 3% Specificity. During atrial flutter the algorithm output was non-AF 94.6% of the time. Due to motion artifacts, the algorithm did not provide AF classification for 36 ± 9% of the 24 hours monitoring. Conclusion: A wrist-wearable device equipped with a PPG and acceleration sensor can provide accurate detection of rhythm irregularities caused by atrial fibrillation in free-living conditions.
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S53: Tuesday, 13 September, 2016
10:30
S53
Chairs: Dewar Finlay and Frans Riepma
Cardiac Condition Monitoring through Photoplethysmogram Signal Denoising Using Wearables: Can We Detect Coronary Artery Disease with Higher Performance Efficacy?
Arijit Ukil*, Soma Bandyoapdhyay, Chetanya Puri, Arpan Pal and Kayapanda Mandana
Aims: For affordable cardiac health monitoring, it is required to ensure accurate cardiac condition detection from wearable-extracted photoplethysmogram (PPG) signals through precise identification, and removal of signal corruptions. We need to prove that analyzing on cleaned (denoised) PPG signal yields significant performance efficacy improvement while performing Coronary Artery Disease (CAD) identification from PPG signal. Methods: It is a mono-signal analysis to identify the morphological trend, emphasizing on individual’s cardiac characteristics. PPG signal is segmented using slope sum function to recognize each cardiac cycle. Further, the most probable segment duration is computed using DBSCAN clustering. Dynamic time warping (DTW) distances between an ideal PPG segment template and each of the PPG segments are derived to isolate the dissimilar segments. Each segment is restricted to most probable segment length to counter non-linearity of the PPG segments. Then Hampel filter, a standard outlier detection method is applied on the computed DTW distances. The detected outliers in the DTW distances are declared as corruption. Corruption Detection Results: We experimented with 10 real-field and 10 MIMICII Physionet Challenge 2015 PPG datasets, each of 5 minute duration. Achieved efficacy of PPG corruption detection: For real-field - Recall (R), Specificity (Sp) and Precision (P) are 79%, 97.4%, 89.4% respectively; for MIMICII - R=80.4%, Sp=96.3%, P=72%. Clinical Utility Results- CAD Identification: We considered 126 PPG signals from MIMCII with 67 CAD and 59 Normal subjects; training dataset: 40 CAD, 30 Normal; test dataset: 27 CAD, 29 Normal. We have chosen Heart Rate and standard deviation of NN intervals –based Heart Rate Variability (extracted from 20 second non-overlapping windows) as the features of linear kernel based Support Vector Machine Classifier. CAD identification results: cleaned PPG datasets: P=51.11%, R=79.31%, F1-score=0.62 and uncleaned PPG datasets P= 43.59%, R=58.62%, F1-score =0.49, which proves higher clinical utility from our method.
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S53: Tuesday, 13 September, 2016
10:30
S53
Chairs: Dewar Finlay and Frans Riepma
Multi-Dimensional Kineticardiography in Simulated Microgravity: Preliminary Results from the ESA-RSL 60 days Bed Rest Study
Pierre-François Migeotte*, Jean Monfils, Federica Landreani, Alba Martin-Yebra, G.K. Prisk, Irina Funtova, Jens Tank, Philippe van de Borne and Enrico Caiani
Head down tilt bed rest (BR) can simulate to some extent the effects of microgravity leading to cardiac deconditioning. We present preliminary results from the first cohort of subjects of the ESA-RSL long duration bed-rest study which were exposed to -6° head down tilt (HDT) during 60 days: Control (Ctrl) group n=7, age 27 +/- 4 y; Training (Tr) group n=5, age 31 +/- 8 y. Tr group was assigned to a daily reactive jump in a sledge jump system while Ctrl was assigned to rest. Cardiovascular responses were assessed during imposed breathing protocols: 10 breath at 4, 6, 8, 10 s, increasing in a stepwise way, performed in supine and sitting before (HDT-4) and at recovery (R+1, R+4) and in the -6° HDT position during the BR period ( HDT+5, 21 & 58). ECG, ICG, ballisto- and seismo-cardiograms were continuously recorded. Phase contrast MRI protocols were also performed (results presented in a parallel paper). We present Multi-dimensional Kineticardiography (MKCG), a novel technique for the wearable monitoring of the mechanical characteristics of the cardiac contraction which consists in measuring the full body kinetic energy (Ktot) in its 6 degrees-of-freedom via a 3-axis accelerometer and gyroscope placed close to center-of-mass. At HDT+5, in Ctrl RR-intervals and Ktot were found significantly increased from 896 to 1076 +/- 34 ms for RRI and from 16 to 33 +/- 5 mJ for Ktot, while for Tr not changes were observed. During recovery, both groups were tachycardic at 728 and 711 +/- 19 ms (Ctrl and Tr respectively), while three fold increase in Ktot to 48 (Ctrl) and 45 (Tr) +/- 3 mJ, were observed. As these results parallels those found for MRI cardiac output, this shows that MKCG has the potential to offer a significant clinical tool for diagnostic and monitoring.
S53: Tuesday, 13 September, 2016
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Chairs: Dewar Finlay and Frans Riepma
Impact of the Mechanical Interface on BCG Signals obtained from Electronic Weighing Scales
Ramon Casanella*, Joan Gomez-Clapers, Marc Hernandez-Urrea and Ramon Pallas-Areny
Aims: In the last years, there has been an increasing interest in periodic monitoring of cardiovascular information at home or in other non-clinical scenarios. Weight scales have been recently proposed for recording the bal-listocardiogram (BCG), a signal caused by the forces in the body as a result of cardiac ejection. Several parameters obtained from the BCG have been correlated to important cardiovascular markers such as the pre-ejection pe-riod, cardiac output or the pulse transit time. Nevertheless, weight scales are second-order mechanical systems whose natural frequency when a subject is standing on them can be lower than the BCG bandwidth hence can yield a distorted recording. This work analyzes the reproducibility of the BCG ob-tained in different weight scales. Methods: The BCG and the ECG have been recorded from 5 healthy subjects (27.2 ± 3.7 years) for 60 s by sequentially using the force sensors of three different commercial weight scales connected to the same signal acquisition system. An ensemble average representative of each subject and weight scale has been obtained by applying Woody’s method with the ECG as timing reference. Results: Consecutive BCG signals obtained with the three scales show consistent systematic intra-subject differences that can reach up to 30 ms in the timing of the J peak. This timing error is relevant because it is about 50 % of the changes induced by typical respiratory maneuvers, such as that of Valsalva, used to modulate hemodynamic parameters in correlation studies between changes in J timing with respect to different cardiac fiducial points. Conclusions: Due to its ubiquity, weighing scales are indeed very promising devices to monitor cardiovascular function at home but their fre-quency response must be accounted for and minimal performance standards should be defined for them.
S54: Tuesday, 13 September, 2016
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Chairs: Paul Rubel and Fabio Badilini
Reproducibility of Heart Rate Variability Characteristics Measured on Random 10-second ECG using Joint Symbolic Dynamics
Muammar Kabir*, Golriz Sedaghat, Jason Thomas and Larisa Tereshchenko
Introduction. The study of heart rate variability (HRV) provides clinically relevant information about autonomic control. Compared to conventional signal-processing approaches which are inadequate for characterizing com-plex system dynamics, joint symbolic dynamics (JSD) has been shown to be an effective technique to provide enhanced information. In clinical practice, 10-second ECG recording is routinely available and therefore could provide clinical studies with the opportunity to investigate clinical utility of HRV characteristics for risk assessment in patients. However, reproducibility of HRV indices using JSD has never been studied. Methods. High resolution (1000Hz) modified (5th intercostal space) Frank orthogonal ECG (XYZ) was recorded at rest in the supine position for at least 3 minutes in 170 healthy participants of the prospective cohort Intercity Digi-tal Electrogram Alliance (IDEAL) study. Two non-adjacent 10-second ECG segments were selected from all ECG recordings. Respiratory signal was derived from the ECG. Parabolic fitting was used to detect ECG R-peaks. Using JSD, time series’ of RR’ intervals and respiratory phases (calculated using Hilbert transform) were transformed into tertiary symbol vectors based on their successive changes and words of length ‘3’ were formed. Bradley-Blackwood test, Lin’s concordance correlation coefficient and Bland-Altman analysis was used to assess the agreement between measured log-transformed JSD characteristics of HRV, and their reproducibility. Results. Traditional HRV measures such as RR’ interval changes showed a very high reproducibility. Agreement between two 10-second JSD indices of HRV was low. Interestingly, a significant decrease in low-high alterations of HRV dynamics measured using JSD was observed when respiratory phase transition intervals were excluded (10s: 4.7±9.4 vs. 24.8±21.0%, p<0.0001; 3min: 9.8±8.1 vs. 24.8±12.3%, p<0.0001). Conclusion. The HRV parameters calculated using JSD have low reproducibility on 10-second ECG. Respiration-induced ECG changes should be considered for the study of HRV symbolic dynamics.
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S54: Tuesday, 13 September, 2016
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S54
Chairs: Paul Rubel and Fabio Badilini
Finding similar ECGs in a large 12-lead ECG database
Richard Gregg*, Sophia Zhou and Saeed Babaeizadeh
Background: Automated matching of a patient’s 12-lead ECG to a large database of 12-lead ECGs to find similar ECGs has many potential appli-cations including 1) help by example; 2) statistical diagnosis; 3) con-firming patient identification; and 4) reviewing the patient’s past ECGs. We report the performance of morphology similarity matching in this study. Method: Only patients with multiple ECGs were selected for the study set. The total number of ECG was 24,262 from 8,663 patients. Average beats were created for each ECG by algorithm. Similar ECGs were found by exhaustive search of pair-wise template matching between the average beat of each ECG and all other ECGs. Similarity reference was the patient identification, i.e. two ECGs were similar if they came from the same pa-tient. Pair-wise template matching was performed over the entire QT in-terval with JT heart rate correction for the heart rate difference. For each ECG, 20 nearest neighbors by template match were extracted from the database. Sensitivities are calculated for finding any and all of the ECGs from the same patient in the set of 20 nearest neighbors. Results: In the exhaustive search, sensitivities were 68% and 37% for finding any and all of the ECGs from the same patient respectively. Conclusion: Pair-wise exhaustive search of template match found similar ECGs with good sensitivity. Further research is needed to determine if acceptable performance in ECG retrieval can be achieved by low com-plexity similarity database search.
S54: Tuesday, 13 September, 2016
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Chairs: Paul Rubel and Fabio Badilini
High Frequency QRS for Detection of Myocardial Ischemia
Pavel Leinveber*, Josef Halamek, Pavel Jurak, Filip Plesinger, Jolana Lipoldova, Juraj Jurco and Miroslav Novak
Introduction: Changes of high frequency components of QRS complex (HFQRS) have been reported as a sensitive indicator of myocardial ischemia. Different markers were suggested. Our aim was to test differences in HFQRS parameters between healthy and coronary artery disease patients (CAD). Methods: 5 min ECG of 106 controls and 103 CAD were analyzed. The data were acquired during rest in supine position with conventional 12-lead ECG (sampling frequency 5 kHz, dynamic range 24 bit and low pass cutoff frequency 2 kHz). Data were analyzed offline. The first step was QRS detection and sorting. Only regular beats were analyzed. Frequency envelopes in frequency band 150-250Hz were computed and averaged to increase SNR. The next parameters were analyzed in each lead in QRS area: Amax: maximal amplitude; RMS in area over 0.1Amax; RAZ: reduced area zone; KURT – kurtosis, statistical parameter of envelope. The mean over defined set of leads was analyzed. Results: The mean ± STD over healthy were 14.7±6.5 µV; 7.6±3.4 µV; 0.41±0.23; 7.1±1.2 for Amax, RMS, RAZ, KURT respectively. The values for CAD were 9.3±4 µV; 4.7±2 µV; 0.58±0.25; 5.7±1.7 for Amax, RMS, RAZ, KURT respectively. Differences between healthy and CAD are highly significant, the P is below 0.00001 for all presented parameters. Maximal differences are for RMS (P<10e-11), minimal for RAZ (P<10e-5). Significant correlation exists between Amax and RMS, independent parameters are KURT and RAZ, the correlation is below 0.5. Discussion: Healthy subjects have significantly higher Amax, RMS, KURT and significantly lower RAZ than CAD. Diagnostic limitation is high inter-subject variability and diagnosis based on measurement only in rest has low specificity and sensitivity. ROC area based on all presented parameters is 0.732. The course of parameters during heart excitation should be considered to improve sensitivity and specificity.
S54: Tuesday, 13 September, 2016
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Chairs: Paul Rubel and Fabio Badilini
Potential Solutions for Managing Real-Time ECG/Arrhythmia Monitoring Alarms - A Review
John Wang*
Electrocardiographic monitoring, which allows for continuous non-invasive detection and documentation of cardiac arrhythmia, is one of the most frequently used monitoring procedures for managing in-hospital patients. The most often cited issue of using these systems is the large number of alarms generated by these systems. These alarms include both false alarms and repetitive non-actionable true alarms. Device based solutions for false alarm reduction include a) providing more specific information in assisting users to identify the root cause of the false alarms, and b) continuing the development of more robust algorithms. In this presentation, useful information that could be provided by the device in supporting root cause identification will be discussed. In addition to the enhancement of existing ECG based algorithms, the devevelopment should also include multi-parameter algorithms that incorporate simultaneous analysis of both ECG and non-ECG signals, such as blood pressure and pleth. Frequent repetitive non-actionable alarms can be reduced and managed by developing a more robust alarm generation structure. While a large amount of work to develop better algorithms has been reported, there have been very limited discussions on the development of a more robust alarm generation structure. This presentation will provide an overview of the key features/components of a robust alarm generation structure and show how such a system could be used to manage and reduce the repetitive non-actionable alarms. Computerized Electrocardiographic monitoring was introduced for clinical use in the 70s. Based on continuous users’ feedback and advancement in computing technologies, commercial systems have improved significantly over the years. As before, it is expected that the identified issues will be the main focus of future development for commercial systems. As discussed, the improvement will come from better user support tools for trouble-shooting, more accurate analysis algorithms including both ECG and multi-parameter based, and better alarm generation structures.
S54: Tuesday, 13 September, 2016
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Chairs: Paul Rubel and Fabio Badilini
Comparison of Spatial QRS-T Angle in Different Healthy Racial Groups
Elaine Clark* and Peter Macfarlane
Aim: A wide spatial QRS-T angle has been associated with higher risk of cardiac death. The aim of the present study was to compare the normal limits of the spatial QRS-T angle in four cohorts of different apparently healthy racial groups to determine if there were any significant differences due to age, gender and race. Methods: The University of Glasgow ECG Analysis Program was used to derive X, Y and Z leads from the 12 lead ECG and hence obtain the spatial QRS-T angle. The analyses were carried out on apparently healthy male and female Black (Nigerian), Caucasian (Scottish), Chinese (Taiwanese) and Indian cohorts. Statistical analysis of the angles was undertaken using SPSS and MedCalc packages. Results: In total, 4223 ECGs were analysed. 37 ECGs were excluded for technical reasons leaving 2542 males and 1644 females aged between 18 and 87 in the study. The mean spatial QRS-T angle for males in Black, Caucasian, Chinese and Indian populations was 66±26°, 69±29°, 59±26 and 72±33° respectively. The mean for Chinese males was significantly lower than for all other groups (P<0.001). For females, the corresponding mean values were 42±23°, 57±25°, 40±22° and 41±25°, with the Caucasian mean being significantly higher than the others (P<0.001). In all ethnic groups, the mean spatial QRS-T angle was higher in males than females, with an overall mean difference of 21°. Mean spatial QRS-T angle generally decreased as age increased in males while the opposite was true for females. The age independent upper limits of normal (98th percentile) were 128°, 145°, 141°, 157° for males and 101°, 119°, 85°,104° for females for Black, Caucasian, Chinese and Indian groups respectively. Conclusion: Race and gender in particular require to be considered when assessing the spatial QRS-T angle.
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S54: Tuesday, 13 September, 2016
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S54
Chairs: Paul Rubel and Fabio Badilini
SCP-ECG V3.0: An enhanced Standard Communication Protocol for computer-assisted Electrocardiography
Paul Rubel*, Danilo Pani, Alois Schloegl, Jocelyne Fayn, Fabio Badilini, Peter Macfarlane and Alpo Varri
Several authors and task forces have repeatedly emphasized the need for open communication and interlinking of various types of ECG devices and systems and the difficulty of overcoming the lack of interoperability and limitations of different standards and proprietary solutions. In this paper, we will report about the progress made by our Project Team in revising and markedly extending the scope of the so called SCP-ECG “Standard communication protocol - Computer-assisted electrocardiography” Norm (EN:1064 ISO 11073-91064). The main goal of the SCP-ECG standard is to address ECG data and related metadata structuring, semantics and syntax, with the objective to facilitate interoperability and thus to support and promote the exchange of the relevant information for unary and serial ECG diagnosis. The standard will now also provide support for the storage of continuous, long-term ECG recordings and afford a repository for selected ECG sequences and the related metadata to accommodate stress tests, drug trials and protocol based ECG recordings. The global and per-lead measurements sections have been extended and three new sections have been introduced for storing beat-by-beat and/or spike-by-spike measurements and annotations. The used terminology and the provided measurements and annotations have been harmonized with the ISO/EEE 11073-10102 Annotated ECG standard. Emphasis has also been put on harmonizing the Universal Statement Codes with the CDISC and the categorized AHA statement codes and the drug and implanted devices codes with the ATC and NASPE codes. Another important feature of the SCP-ECG standard is to provide a protected format including self-control capabilities of the content and preserving confidentiality during the exchange on account of its dedicated binary representation. The latter also yields for files of small size, compliant with mHealth scenarios for an early detection of cardiac diseases, anywhere and anytime.
S55: Tuesday, 13 September, 2016
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S55
Chairs: Remi Dubois and Dana Brooks
Noninvasive Localization of Premature Ventricular Activity Using Different Equivalent Point Sources
Jana Svehlikova* and Milan Tysler
The aim of the study was to compare localization errors of inverse estimations of the origin of premature ventricular contraction (PVC) using three different formulations of transfer matrix between the equivalent source and the surface potentials. Body surface potential maps (BSPMs) provided in EDGAR database by Karlsruhe Institute of Technology were used. The ECG signals were measured in 63 precordial leads during nine spontaneous PVCs in one patient. From the ablation procedure two reference points were known: PVC1– the site where the earliest activation time was recorded and PVC2– the site of the latest successful ablation. The geometry of patient’s heart and torso were provided together with the transfer matrices for epicardial potentials (EPs) and transmembrane voltages (TMVs) on the joined endo-and-epicardial surface. The transfer matrix for dipoles (DIPs) situated in the mesh within the myocardial volume was also computed. The only constraint for the inverse solution was the assumption that at the beginning of the PVC only very small area is depolarized and it can be represented by a single point source. The inverse solution was computed for all available positions of the sources and the best source was chosen according to the criterion of the smallest relative residual error (RELDIF) between the input BSPM and the map generated by the equivalent source. The localization error (LE) of the inverse solution was evaluated with respect to both reference points. For all nine considered PVCs the locations of the inverse results were very stable – for particular transfer matrix they resulted in the same point or in adjoining points for all cases. Mean LEs with respect to PVC1/PVC2 were 22mm/15mm for EPs, 26mm/16mm for TMVs and 25mm/25mm for DIPs. The LEs of the PVC origin obtained by inverse solution supposing single point source were similar regardless of the source formulation.
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S55: Tuesday, 13 September, 2016
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Chairs: Remi Dubois and Dana Brooks
Noninvasive Epicardial and Endocardial Electrocardiographic Imaging of Scar-Related Ventricular Tachycardia
Linwei Wang, Omar Gharbia, Sandesh Ghimire*, Milan Horacek and John Sapp
Background: Ventricular tachycardia (VT) is a major cause of morbidity and mortality in patients with heart disease. Many life-threatening VTs involve a “short circuit” sustained by heterogeneous scar substrates. To treat VT and prevent its recurrence, it is effective to interrupt the VT circuit by catheter ablation. Critical components of the circuit, ideally, can be delineated during VT using a combination of VT and entrainment mapping. To do so with invasive catheter mapping, however, requires the VT to be stable over a period of time. This unfortunately is only possible in a small percentage of patients. A noninvasive approach to quickly map VT has the potential to allow the mapping of more VTs and to improve the success rate of catheter ablation. Methods: In the presented workflow, patients first undergo a standard axial CT scan. 120-lead ECG mapping is then obtained during the initial induction of clinical VTs at the beginning of an ablation procedure. Patient-specific biventricular model and body-surface electrode positions are obtained from CT images. Noninvasive ECG imaging then computationally reconstructs electrical signals in the heart using 120-lead ECGs obtained during induced VT. Post-analysis is carried out to derive the activation time, conduction velocity, and phase maps for visualizing the resulting reentry circuits. Results & Conclusions: Experiments were conducted on three patients who underwent ablation of scar-related VT. In a retrospective study, inverse results computed from 120-lead ECGs were analyzed to examine the re-entry rotation, exits, and entrances of the VT circuits. These results were shown to be consistent with the region of scar and critical VT sites identified from ablation procedures (Figure 1). This pilot study shows that noninvasive ECG imaging has the potential to provide fast VT mapping for stable and unstable VTs. It may allow a better understanding of VT mechanisms and improve ablation efficacy.
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S55: Tuesday, 13 September, 2016
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S55
Chairs: Remi Dubois and Dana Brooks
A Comparison of Discretization Methods for the Inverse Problem of Electrocardiography
Laura Bear*, Leo Cheng, Remi Dubois, Denis Loiselle and Bruce Smaill
Aims: The inverse problem of electrocardiography reconstructs cardiac electrical activity from torso potentials. Here we compare the two most common methodologies used for this problem; the boundary element method (BEM) and the method of fundamental solutions (MFS). Methods: Torso and epicardial potentials were recorded simultaneously in closed-chest pigs (n=5), during sinus rhythm, epicardial, and endocardial pacing (70 records in total). Post-mortem MRI was used to construct experiment-specific torso and epicardial meshes and to determine electrode locations. Three inverse methods were examined for each animal: 1) a BEM inverse using a refined torso mesh, with kriging interpolation to map potentials from torso electrodes to nodes, 2) a standard MFS inverse (MFSstand) using torso electrodes as direct inputs, and 3) an MFS inverse using the refined torso mesh and interpolated signals (MFSfull). In each case, potentials were reconstructed using Tikhonov regularization and CRESO criteria. Reconstructed electrograms and activation time (AT) maps were compared to their recorded signals using relative errors (RE) and correlation coefficients (CC). Results: Potential magnitudes were significantly underestimated by BEM (RMSvoltage=1.81±0.51 mV) compared to those measured (RMSvoltage=4.47±1.03 mV; p<0.0001). The general shape of electrograms were captured (CC=0.54±0.10) as was the spread of activation (CC=0.73±0.12 for AT Maps), though the total activation duration was underestimated (41±12 ms; p<0.001) and pacing sites were not localized reliably (27±21 mm; p<0.001). MFSfull improved potential magnitudes (RMSvoltage=2.07±0.46 mV; p<0.0001), though there was no significant difference in electrogram shape. There was also a significant improvement in localization of pacing sites (LE=19±10 mm; p=0.01). There was no significant difference in any metric between MFSfull and MFSstand. Conclusion: The BEM and MFS demonstrate similar accuracy for reconstructing epicardial potentials, with minor improvements by the MFS. Considering this, in addition to the advantage of being meshless, MFS is the preferred approach for inverse problems.
S55: Tuesday, 13 September, 2016
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Chairs: Remi Dubois and Dana Brooks
The Consortium on Electrocardiographic Imaging
Jaume Coll-Font*, Dana H Brooks, Peter M van Dam, Jwala Dhamala, Olaf Dössel, Maria de la Salud Guillem Sánchez, Rob MacLeod, Danila Potyagaylo, Walther Schulze, Jess D Tate and Linwei Wang
ElectroCardioGraphic Imaging (ECGI) has received increasing academic, clinical, and industrial attention recently. However, for ECGI to be more widely adopted in clinical practice, it is necessary to address the problems of reproducibility, cross-lab validation, and cross-lab cooperation. This challenge is difficult given that each group uses separate datasets, algorithms, software, and, often, different validation metrics. It is thus necessary to establish a generally accepted infrastructure that allows shared access to datasets, methods, and experimental knowledge. We created the Consortium on Electrocardiographic Imaging (CEI) in 2015 for this purpose and are working to attract all research groups exploring ECGI. CEI has two main infrastructure components to tackle these challenges: a public collection of datasets, called EDGAR, and workgroups organized around common interests. Datasets from 6 groups from 3 continents are currently available from EDGAR in a standardized format including data from realistic simulations, large animal models, and experimental and clinical human subject data. The workgroups tackle validation of forward problems and inverse solutions, localization of first activation site in Premature Ventricular Contractions (PVCs), and imaging of Atrial Fibrillation (AF). The first workgroup aims to identify sources of uncertainty in forward models by comparing results at every step of the pipeline from segmentation of anatomical scans to computation of the forward matrix. The second workgroup aims to generate validation benchmarks for inverse solutions to test accuracy and utility of inverse solutions to localize initial activation sites of PVCs. The third group aims to establish benchmarks for imaging of atrial activity and AF. CEI also organizes international meetings and hackathons, either standalone or in conjunction with existing meetings such as Computing in Cardiology. The CEI is continuing to develop infrastructure to facilitate collaboration and foster reproducibility within the ECGI community. For more information about CEI, visit www.ecg-imaging.org or join the mailing list info@cei.org.
S55: Tuesday, 13 September, 2016
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Chairs: Remi Dubois and Dana Brooks
Temporal Dilation of Animal Cardiac Recordings Registered to Human Torso Geometry
Karli Gillette, Jess Tate*, Brianna Kindall, Wilson Good, Jeff Wilkinson, Narendra Simha and Rob MacLeod
Introduction: Data attained in electrophysiology studies of animals is useful to understand the mechanisms of cardiac diseases, particularly if adjusted to fit within human torso geometries. However, when large animal heart geometries are registered to a human torso model, timing of the electrograms must be adjusted to avoid an apparent increase in conduction velocity resulting from increased heart size. We developed a time dilation technique to ensure that adjusted cardiac electrograms were physiologically similar to human recordings after registration. Methods: We acquired electrograms from ten exposed canine hearts using an epicardial sock and registered a triangle mesh of the electrode locations to a single human torso geometry. We then calculated a global temporal scaling factor from the median change in length for each triangular mesh edge. Linear dilation was performed on the cardiac recordings for each data set using the calculated scaling factor. We validated the results with conduction velocity, QRS width, and QT interval for the dilated electrograms compared to literature values in humans. Results: Linear temporal dilation of the canine cardiac recordings yielded signals resembling human recordings. The mean temporal scaling factor, weighted based on the number of data sets per geometry, was 1.73$\pm$0.02. Wave morphologies of dilated cardiac recordings resembled human recordings and were also quantitatively comparable. The conduction velocity of 31.3$\pm$1.5 cm/s before registration and dilation increased to 39.6$\pm$2.5 cm/s after. The original canine cardiac recordings showed a QRS width and QT interval of 43.8$\pm$0.6 ms and 175$\pm$8 ms, respectively. After registration, the predicted values were 76$\pm$10 ms and 310$\pm$10 ms. Conclusions: Temporal correction of canine epicardial recordings can be used to generate signals similar to human recordings. Epicardial potential mapping of dilated canine signals allows the investigation of human-like arrhythmias and other disease states that can not be readily induced or measured in humans.
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S55: Tuesday, 13 September, 2016
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Chairs: Remi Dubois and Dana Brooks
Patient-Specific Time-Varying Association between Spatial and Temporal Variability in Repolarization and High Sensitivity Troponin I
Larisa Tereshchenko* and Albert Feeny
Introduction: Fast cell-to-cell uncoupling in response to acute myocardial injury is adaptive as it prevents the spread of chemical mediators of injury from severely affected areas to less affected areas, and therefore decreases damage to the heart. Cell-to-cell uncoupling is characterized by increasing repolarization lability (RL). Hypothesis: We hypothesized that the RL, quantified by spatial TT’ angle, is associated with the degree of myocardial damage, quantified by the level of high sensitivity troponin I (hsTnI), in acute coronary syndrome (ACS) and acute decompensated heart failure (ADHF). Methods: Spatial TT’ angle on resting 12-lead ECG (transformed to vectorcardiogram) and hsTnI were measured simultaneously every 3 hours during a 12-hour observation period in a prospective cohort of emergency department patients (n=379; age 57.8±13.2y; 54% female, 64% black), diagnosed with ACS(n=28), ADHF(n=35), or a non-cardiac condition(n=316). Random-effects linear regression assessed the association of spatial TT’ angle and myocardial injury, with adjustment for demographics (age, sex, race), prevalent cardiovascular disease (myocardial infarction, history of revascularization, stroke, HF), risk factors (diabetes, smoking, hypercholesterolemia, hypertension, cocaine use), and left bundle branch block. An adjusted multinomial logit model was used to characterize differences between ACS, ADHF and non-cardiac conditions. HsTnI and TT’ angle variables were log-transformed to normalize distribution. Results: As compared to acute non-cardiac conditions, ADHF was characterized by significantly higher baseline RL (adjusted relative risk ratio (RRR) for TT’ angle 5.6(95%CI 1.2-25.4); P=0.027). Baseline RL in ACS did not differ from non-cardiac conditions (RRR 0.8(95%CI 0.2-4.0); P=0.770). A 10-fold increase in hsTnI was associated with a 1.14(95%CI 0.16-2.11) degrees increase in spatial TT’ angle (P=0.022). High (above median) HsTnI in ACS was characterized by significantly larger TT’ angle (12±8 vs 5±2 degrees; P=0.01) 12 hours after admission, but not earlier. Conclusion: Spatial TT’ angle is associated with the level of hsTnI in ACS and ADHF.
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P61: Tuesday, 13 September, 2016
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An Adaptive Organization Index to Characterize Atrial Fibrillation using Wrist-Type Photoplethysmographic Signals
Sibylle Fallet*, Mathieu Lemay, Philippe Renevey, Célestin Leupi, Etienne Pruvot and Jean-Marc Vesin
Introduction: Photoplethysmography (PPG)-based wrist monitors have gained a lot of popularity as portable heart rate monitors. However, their ability to diagnose cardiac arrhythmias, such as atrial fibrillation (AF), is still unexplored. This study aims at quantifying the level of organization of PPG signals during electrophysiology procedures and to assess its potential to characterize atrial fibrillation (AF) episodes. Methods: The database includes 11 adult patients undergoing catheter ablation of cardiac arrhythmias. PPG signals were recorded using a wrist-type sensor, also including an accelerometer. A 12-lead ECG acquired simultaneously with the PPG waveforms was used as gold standard. ECGs were annotated by experts and selected segments were divided into 4 categories: sinus rhythm (SR), regularly paced rhythm (RPR), irregularly paced rhythm (IPR) and AF. The PPG adaptive organization index (AOI), defined as the ratio of the power of the fundamental frequency and the first harmonic to the total power of the pre-processed PPG signal, was computed using adaptive band-pass filters. The AOI was averaged on 10-second epochs (50% overlap). Accelerometer signals were used to remove epochs with motion artifacts. Results: A total of 1779/256/852/268 epochs were considered for AF/SR/RPR/IPR classes. The following mean AOI values were measured: 0.48±0.12 for AF, 0.66±0.23 for SR, 0.78±0.20 for RPR and 0.62±0.19 for IPR classes. Importantly, the AF AOI was significantly smaller than that of the other categories (p<0.001), indicating a higher degree of disorganization. After binary logistic regression, the AUC of the ROC was 0.82 between AF and the other classes. Conclusion: These preliminary results suggest that AF is characterized by a higher degree of disorganization of PPG signal similarly to that of ECG signals. PPG-based wrist monitors appear as promising diagnostic tools for the screening of AF in large populations.
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P61: Tuesday, 13 September, 2016
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Imaging Photoplethysmography: What are the Best Locations on the Face to Estimate Heart Rate?
Sibylle Fallet*, Virginie Moser, Fabian Braun and Jean-Marc Vesin
Purpose: The potential of imaging photoplethysmography (iPPG) for cardiovascular monitoring applications has been highlighted these last years. Different processing schemes have been proposed to extract heart rate (HR) from a defined region of interest (ROI) on the face. However, the reasons that motivate the choice of the ROI are often unknown. This study aims at comprehending the spatial distribution of the HR-related information on the subject face. Methods: The database is composed of six 4-minute video-sequences, from three subjects performing handgrip test or modulating their respiration according to a given protocol. For each video-sequence, a rectangle was manually fitted around the whole face and divided into 260 rectangular ROIs. For each ROI, the iPPG signals were obtained by averaging the pixels, in each frame. The resulting signals were band-pass filtered (0.6-4 Hz). The reference HR was derived from the ECG acquired simultaneously with the video-sequences. A power spectral density (PSD) analysis was performed to determine the amount of HR-related information in each ROI. For this purpose, a 10-second sliding-window (50% overlap) was used to compute the PSD of the iPPG signals. For each window, the percentage of the total power in a defined frequency-band centered at the local true HR was calculated and then averaged for each subject (PPow). Results: Normalized color maps were used to visualize the spatial distribution of the HR-information and clearly showed that color fluctuations due blood volume changes are always more pronounced on the forehead region. After face segmentation, for the R/G/B channels, averages PPow of 27%/43%/27% for the forehead, 17%/28%/18% for the cheeks and 16%/24%/16% for the whole face regions were obtained. Conclusion: Numerical results showed that the forehead part is the most relevant region to estimate HR, followed by the cheekbones. These regions should be tracked in priority in iPPG applications.
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P61: Tuesday, 13 September, 2016
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Real-Time Approaches for Heart Rate Monitoring using Imaging Photoplethysmography
Sibylle Fallet*, Leila Mirmohamadsadeghi, Virginie Moser, Fabian Braun and Jean-Marc Vesin
Purpose: Imaging photoplethysmography (iPPG) has gained a lot of popularity as a contactless heart rate (HR) monitoring technique. However, most of the existing approaches are based on block-wise processing, which is not optimal for real-time applications. In this study, three different algorithms suitable for almost real-time HR estimation are proposed and evaluated on a database composed of video-sequences acquired in different experimental conditions. Methods: The database is composed of 46 4-minute video-sequences recorded in visible light using an RGB camera or in darkness with a near-infrared camera and appropriate illumination. In order to induce changes in HR, the subjects were asked to perform handgrip exercise or to modulate their respiration according to a given protocol. The iPPG signals were obtained by averaging the pixels within a fixed region of interest selected on the forehead. Three algorithms for continuous HR estimation are investigated: 1) an algorithm based on adaptive sliding-window singular value decomposition (SWASVD), 2) an approach based on an adaptive band-pass filter (OSC-ANF-W), 3) a notch-filter bank (NBF) estimation method. In addition, a confidence index was developed to eliminate motion artifacts. The ground-truth HR was derived from the ECG signal acquired simultaneously with the videos. Results: For the visible/dark sequences, average absolute errors (AAE) of 3.42/5.25, 3.14/4.21 and 3.98/6.02 bpm were obtained for the SWASVD, the OSC-ANF-W and the NFB algorithms, respectively. The corresponding averaged estimation delays, estimated using the cross-covariance between true and estimated HR, were 4 seconds (SWASVD and OSC-ANF-W) and 3 seconds (NFB). Conclusion: Although the proposed algorithms are based on different mechanisms, they lead to similar results. Moreover, the HR fluctuations induced by the modulation of the breathing rate or the handgrip were correctly tracked. These results highlight the potential of iPPG for real-time HR monitoring applications, both in visible light and darkness using near-infrared light.
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P61: Tuesday, 13 September, 2016
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Missing Data Imputation for Individualised CVD Diagnostic and Treatment
Sitalakshmi Venkatraman, Andrew Yatsko, Andrew Stranieri and Herbert F Jelinek*
Cardiac health screening standards require more and more clinical tests consisting of both blood, urine and anthropometric measures as well as an extensive clinical and medication history. Extensive screening requires diagnostic determinants to be highly accurate to reduce false positives and ensuing stress to the individual patients. In addition, it requires algorithms that allow imputing missing variables on an individual basis. The current study provides a unique imputation algorithm that can be applied to personalised cardiac health screening. The algorithm is based on dynamic clustering centred around cardiovascular disease (CVD), diabetes mellitus and hypertension, conditions. The DiabHealth database containing 6800 records with 200 attributes was used for testing the experimental validity of our algorithm. Our results for predicting CVD showed a high accuracy with a sensitivity and specificity 92% and 99% respectively using the Info-Neighbour method. Naïve Bayesian performed less accurately (80% and 84% respectively) and identified Framingham cardiac risk as the best predictor. Removing variables that define cardiac events and conditions available from the medical history left age followed by use of anti-hypertensives and anti-cholesterol medication, especially statins as the best predictors. The missing values algorithm is an important addition to patient-centred healthcare in the current population screening environment since it allows the prediction of CVD in individual patients who do not provide all the required cardiac health predictor variables.
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A Heuristic Gene Regulatory Networks Model for Cardiac Function and Pathology
Armita Zanegar, Peter Vamplew, Andrew Stranieri and Herbert F Jelinek*
Genome-wide association studies (GWAS) and next-generation sequencing (NGS) has led to an increase in information about the human genome and cardiovascular disease. Understanding the role of genes in cardiac function and pathology requires modeling gene interactions and identification of regulatory genes as part of a gene regulatory network (GRN). Feature selection and data reduction not sufficient and require domain knowledge to deal with large data. We propose three novel innovations in constructing a GRN based on heuristics. A 2D Visualised Co-regulation function. Post-processing to identify gene-gene interactions. Finally a threshold algorithm is applied to identify the hub genes that provide the backbone of the GRN. The 2D Visualized Co-regulation function performed significantly better compared to the Pearson’s correlation for measuring pairwise associations (t=3.46, df=5, p=0.018). The F-measure, improved from 0.11 to 0.12. The hub network provided a 60% improvement to that reported in the literature. The performance of the hub network was then also compared against ARACNe and performed significantly better (p=0.024). We conclude that a heuristics approach in developing GRNs has potential to improve our understanding of gene regulation and interaction in diverse biological function and disease.
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A Novel Algorithm for Fast Ballistocardiogram Cycle Extraction in Ambulatory Scenarios
Joan Gomez-Clapers, Ramon Casanella* and Ramon Pallas-Areny
Aims: The ballistocardiogram (BCG) is the recording of forces in the body as a result of cardiac ejection and can be obtained from modified weight scales to deliver cardiovascular information in ambulatory scenarios. However, such BCG recordings are burdened by artifacts whose effect is often minimized by ensemble-averaging techniques that rely on reference signals such as the electrocardiogram (ECG), not easily available in non-clinical settings. This work presents a novel algorithm (JDet) for BCG cycle extraction intended for fast generation of ensemble averages in ambulatory scenarios. Methods: The sensitivity and positive predictivity of JDet were evaluated for recordings from 14 healthy subjects standing on a modified weight scale and the results compared to those from BSeg++, a BCG cycle-extraction algorithm that does not require any reference signal either. Afterwards, the signal to noise ratio (SNR) was calculated for ensemble averages synchronized from fiducial points obtained from JDet, BSeg++, and the ECG for different recording durations. Results: The sensitivity of JDet is better than that of BSeg++ (0.87 vs. 0.57) whereas their positive predictivities are similar (0.92 and 0.87). The SNR for ensemble averages generated from JDet are similar to ECG-generated ensemble averages for short recordings due to its higher sensitivity compared to BSeg++. For long durations, SNR is limited by false positives and trends towards a value similar to that of BSeg++. SNR for ensemble averages generated from JDet can be close to that of those synchronized to the ECG, the only cost being a 25 % longer recording time whereas BSeg++ needs recordings about 100 % longer. Conclusions: The JDet algorithm enables faster and more reliable measurements of cardiovascular parameters from the BCG in ambulatory scenarios without any ancillary reference signal. The results provide guidelines for further improved algorithms intended for short recordings.
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A Non-rigid Electro-anatomic Map and CT Surface Registration Method
Lixia Shu* and Changyan Lin
Aims: Electro-anatomical map (EAM) and CT surface registration is widely used for catheter navigation in atrial fibrillation (AF) ablations. However, few studies have done on the registration algorithm. Furthermore, these methods are inaccurate for precise navigation. The reason is that the transform models they use, rigid or affine transformation, can’t accurately describe the large elastic atrial deformations. Therefore, in this study, we applied an Incremental Free Form Deformations (IFFD) model, and proposed an IFFD based non-rigid method for accurate EAM and CT surface registration. Methods: Firstly, using rigid transform and pricipal axes based approach, EAM and CT surface were coarsely aligned. EAM was the float point set; CT surface was the reference set. Secondly, using Sum of Squared Differences (SSD) as the similarty measurement and cubic B-spline based local IFFD as the tranform model, EAM and CT surface were finely aligned. Different from the coarse step, EAM was the reference point set, and CT surface was the float set. Those IFFD parameters that minimized the objective function, the sum of SSD and a smoothness term, were the final registration result. Results: Using Carto-Merge, stochastic approach and IFFD based method, we registered a simulated EAM/CT pair and a real EAM/CT pair. Root Mean Squre Error (RMSE) of the gold-standard points was applied for evaluating simulated data registration accuracy; average distance between the two point sets was applied for evaluating real data registration accuracy. The RMSE of Carto-Merge, stochastic approach and IFFD based method were 30.297mm, 11.762mm, and 1.525mm. The average distance of Carto-Merge, stochastic approach and IFFD based method were 10.815±7.8371mm, 7.6249±4.7337mm and 2.3152±1.7035mm. For both simulated and real data, IFFD based method obtained much more accurate results than the other two appraches. Conclusion: Compared to the traditional methods, IFFD based method is much more accurate for precise catheter navigation.
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Photoplethysmography as Primary Tool for Progressive Haemorrhage Assessment During Progressive Lower Body Negative Pressure
Kian Davoudi Rad* and Bozena Kaminska
Lack of a precise index to identify degree of hemorrhage prior cardiovascular collapse is being considered a driving cause of fatality in patients experiencing progressive hemorrhage. The traditional clinical hemorrhage assessment consists of conventional beat-to-beat heart rate and arterial blood pressure measurement. But, as shown in [1][2], prior cardiovascular collapses, these indexes continue projecting no significant shift in their status. Hence, Convertino and Tavakolian have shown that Seismocardiography (SCG) and Photoplethysmography (PPG) indeed provide such a window to alarm cardiovascular collapse prior radical projection on conventional measurements. Hence, as author has shown in [3], a mechanically flexible PPG sensor was designed and optimized for continuous monitoring of cardiovascular and respiratory performance. But, the reliability of this sensor for calcification of stages of hemorrhage, was not assessed. Thus, goal of this dissertation was to resolve this issue, by conducting Lower Body Negative Pressure (LBNP) to stimulate hemorrhage in 10 awaked patients and compared the reliability of PPG signal captured from mechanically flexible sensor, with conventional PPG captured from FDA approved pulse oximeter. Results from Bland and Altman (BA) analysis showed all data points from PPG were close to the mean value and between the upper and lower limit of standard deviation BA analysis. The BA between flexible PPG and Nasal respiratory sensor, showed, 0.2 Mean, -2.37 and 2.78 for lower and upper boundaries respectively. Thus, the results demonstrate that the flexible PPG sensor is reliable for detection of respiration rate from PPG sensor during progressive hypovolemia on awaked patients.
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Automatic Classification and Prediction of Congenital Heart Disease based on Hybrid Neural Network System
Wenping Pan*, Kuanquan Wang, Henggui Zhang, Cunjin Luo, Qince Li and yongfeng yuan
Introduction: Clinical study found that in the treatment of congenital heart disease (CHD), the physiological indicators, including B-type natriuretic peptide (BNP), ventricular end diastolic diameter (VEDD), ventricular ejection fraction (VEF) and the size of the hole of congenital heart defects (SHCHDs), have great relevance to each other. Currently, a valid model is needed to be established to predict SHCHDs, indicating the severity of patients concerned, using BNP, VEDD and VEF. Methods and Results: Three different networks, including BP neural network, RBF neural network and Hopfield neural network, were used to process the same clinical data sets respectively. Then, Hybrid Neural Network (HNN) was built to integrate the three outputs produced above by weighted average method decided by the respective average errors. The clinical data sets had covered three types of CHD: ventricular septum defect (VSD), atrial septum defect (ASD) and patent ductus arteriosus (PDA). We had 51 training samples and 20 test samples for VSD, 39 training samples and 32 test samples for ASD, and 31 training samples and 32 test samples for PDA. The average SHCHDs prediction errors of BP, RBF, Hopfield and HNN respectively were as followed (unit is mm): VSD(4.3980,3.2205,3.9491,3.0203),ASD(4.2572,4.1318,4.0167,3.7 274),PDA(4.1318,4.2129 3.8592,3.6658)? Conclusion: The results suggest that HNN significantly improves the generalization ability, and improves the accuracy of automatic diagnosis in the SHCHDs prediction of congenital heart disease.
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Validation of the Heart-Rate Signal Provided by the Zephyr BioHarness 3.0
Daniele Nepi, Agnese Sbrollini, Angela Agostinelli*, Elvira Maranesi, Francesco Di Nardo, Sandro Fioretti, Paola Pierleoni, Luca Pernini, Simone Valenti and Laura Burattini
The Zephyr BioHarness 3.0 (BH3) is a popular wearable system specifically designed for training optimization of professional athletes. If clinical reliable cardiac signals were provided, BH3 could also be used as a practical tool for clinical cardiac-risk evaluation. Thus, the aim of the present study, which is part of larger project on BH3 validation, is to evaluate the reliability of the heart-rate signal (HRS) provided by BH3. To have some levels of heart-rate variability, 10 healthy subjects (age: 34±17 years) were monitored during a 5-min rest. BH3 recorded the electrocardiogram and then applied unknown algorithms in order to obtain and provide HRS (HRS_BH3). Since the tachogram represents the standard signal for studying heart rate and heart-rate variability, we analyzed the electrocardiogram provided by BH3 in order to get the tachogram (HRS_TG). HRS_BH3 and HRS_TG were then compared in terms of mean heart rate (MHR), heart-rate standard deviation (HRSD) and HRSD error (here defined as the difference between HRSD values provided by HRSD_BH3 and HRS_TG, respectively). HRS_BH3 and HRS_TG provided comparable MHR (73.07±15.53 bpm vs 72.86±15.57 bpm, respectively; P=0.1299) while HRSD by HRS_BH3 (4.51±2.28 bpm) was significantly lower than HRSD by HRS_TG (5.63±2.99 bpm; P<0.0043). HRSD error was always positive (from 0.20 bpm to 3.00 bpm), and thus significantly greater than zero (P=0.0043); moreover, it was strongly correlated to HRSD by HRS_TG (?=0.82, P=0.0036). Thus, according to our results, BH3 provides reliable MHR estimations while significantly underestimates heart-rate variability (here measured as HRSD). Specifically, the level of the underestimation linearly grows with the amount of variability. Consequently, the use of BH3 is appropriate to sport applications relying on MHR estimations, but not to clinical evaluations based on heart-rate variability measurements. A larger number of subjects monitored under different conditions will be used in future studies to confirm these results.
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An Evaluation of Different Coating for TiN Microelectrode Chambers Used for Neonatal Cardiomyocytes
Ondrej Svoboda*, Josef Skopalik, Larisa Baiazitova, Eva Gabrielova, Vratislav Cmiel, Ivo Provaznik, Zdenka Fohlerova and Jaromir Hubalek
INTRODUCTION: Neonatal myocytes are widely used model for modern in-vitro pharmacological screening and tissue engineering of cardiac tissue. However, the recording of neonatal myocyte morphology and electrophysiology in real time is still not ideally optimized. The aim of this study was to evaluate the impact of using different substrates in culture chamber on the surviving and functional electrophysiological activity of the myocytes in first 5 days. METHODS: Cardiomyocytes were isolated from 2-day neonatal rat, plated at 6×105 cells/cm2 density on 12×12 ITO microelectrode chamber and cultured for 3 days at 37°C and 5% CO2. Two chamber designs were used: i) 30 µm electrode diameter with 100 µm electrode spacing and ii) variant 30/10 µm. Four surface treatment methods were used: i) collagen IV; ii) poly-L-lysine (PLL); iii) poly-D-lysine (PDL); iv) poly-D-lysine+fibronectin. Cell adhesion, morphology and electrical response were monitored with Olympus IX73 (Calcein AM were used for viability staining). For electrical monitoring 120 channels MEA2100 system were used. Signal baseline were recorded in 0,09% glucose buffer for 300 seconds, thereafter 0,9% glucose buffer were replaced and recorded for spontaneous activity. After that 200 µs duration biphasic electrical pulse was applied with different amplitudes and frequencies. Records were than analysed in point of shape, frequency and amplitude. RESULTS: The PDL+fibronectin treatment display the highest cardiomyocyte adhesion to the electrodes (20% of cells) and developing of contractible cells with measurable electrical response. In these type of samples, cells can be desensitized with 500 mV pulses at 16.67 mHz frequency and recovered after 10 minutes in 0.9% glucose buffer. Pure PDL also provides good electrode adhesion (16%) and lower cell responses can be recorded. Colagen IV and PLL display due to the weak interactions with surface very low cell adhesion (0.5~5%). Cell response cannot be recorded in these Colagen IV and PLL samples.
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A Context-aware, Predictive and Protective Approach for Wellness Monitoring of Cardiac Patients
Abdur Rahim Mohammad Forkan and Weichih Hu*
Cardiovascular diseases are major cause of deaths throughout the world. In this work, we develop a context-aware system for wellness monitoring of older adults who leave alone in home and suffers from cardiac disease. The focus here is the integration of social networking services with conventional remote monitoring services by utilizing a scalable cloud platforms. The goal here is to expand patient's social linkage by identifying similarity in his/her cardiac conditions. Here we build a cloud-oriented context-aware model that captures health parameters such as heart rate, ECG, activity, calories burned using modern fitbit device and ECG sensors. The raw data are sent the cloud platforms provided by Amazon Web Service (AWS) where data is converted to high level context. Using social networks this high level context information is send to patient's friends, family and doctors who are interested to know about his/her health condition. The interested parties get notified by Facebook when the context-aware system detects any changes. That is, using this platform a cardiac patient who live alone and need continuous monitoring is always get connected with virtual community by means of his/her health information. To retain the privacy context data is only sent to the people of known virtual community. This is a new model that utilizes the context data generated by wearable sensors to create interesting social networking services. The system is also designed to promote cardiac patients to interact with their community of interest using various context-aware social services. The results obtained for this innovative model show a new approach of wellness monitoring using social networks.
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Fully-Textile Polymer-Based ECG Electrodes: Overcoming the Limits of Metal-Based Textiles
Danilo Pani*, Andrea Achilli, Pier Paolo Bassareo, Lucia Cugusi, Giuseppe Mercuro, Beatrice Fraboni and Annalisa Bonfiglio
In recent years, there has been a particular interest in wearable electronics with applications in various fields as fashion, fitness or medical devices. The ultimate goal is the integration of sensors and electronics in clothes and garments. For ECG signals acquisition, the disposable Ag/AgCl gelled electrodes are still the gold standard for clinical and short-term recordings. However, their short operation time and low comfort limit their use in wearable applications. In order to overcome these limitations, several groups have been working in the development of dry electrodes using electro-conductive textiles. The development of textile electrodes, typically exploits finished fabrics, woven or stitched with fine metal wires, or silver-coated fibers. Beyond the limited comfort due to the presence of a metallic material in contact with the skin, the skin-electrode interface is less efficient than gelled Ag/AgCl electrodes, motivating the use of solid hydrogel membranes in some studies. In this work, textiles electrodes for ECG are obtained by treating finished fabric with the conductive polymer poly-3,4- ethylenedioxythiophene doped with poly(styrene sulfonate) (PEDOT:PSS). The intrinsic ionic conductivity of the PEDOT:PSS coated fabrics eliminates the need of liquid electrolytes and solid hydrogel for acquiring bioelectrical potentials directly from the human skin, improving both comfort and signal quality. Different procedures for the electrodes fabrication are compared, including a novel printing technique able to achieve good definition and control over the quantity of deposited polymer as valuable alternative to the treatment of the whole tissue. The electrodes have been characterized and then tested on voluntary subjects. A comparative analysis from a clinical perspective reveals that these electrodes can be effectively used to acquire ECG signals with an acceptable quality, highlighting virtues and vices of the proposed technology.
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Design and Implementation of a Tool for the Analysis and Management of Cardiac Parameters
Jorge Aguilera Perez* and Rene Ivan Gonzalez-Fernandez
The aim of this paper is to discuss the main features of a desktop application designed to study the evolution of heart diseases in the community based on the evolution of a group of electrocardiographic parameters. Periodically, a rest ECG is acquired from persons prone to suffer a heart disorder or who have already had a heart attack. Cornell and Sokolov indexes are computed to study ventricular hypertrophy; spatial dispersion of QT interval is calculated to predict malignant arrhythmias and the Selvester score is computed for persons who have suffer a myocardial infarction. Trend charts are updated for each parameter and physicians can analyze the evolution of these cardiac disorders. Also each ECG can be displayed in different formats in order to be checked by the physicians. The Qt Creator platform, a SQL database engine and C++ language were used to develop the proposed application. Several graphical tools were developed to study the ECG and for data representation. Also, a wide set of PDF reports can be generated or printed directly using a printer. A simple protocol designed by the authors is used in the communication process among Cuban ECG machines and the proposed application. The protocol is composed by different types of blocks with the following format: one-byte identification, data bytes, a one-byte checksum and an ending code. The proposed application has been preliminary tested with thirteen healthy voluntaries and two cardiac patients; ten ECGs were acquired for each person and stored in the database. The communication among the proposed application and the ECG machines never failed and all data were reliable stored and processed. Data recovery for physician analysis was easy and according to the expert using the proposed application, it seems a useful tool to predict cardiac disturbances in the community.
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An Interactive Clinician-friendly Query Builder for Decision Support During ECG Interpretation
Ronald Cloughley, Raymond R. Bond*, Dewar D. Finlay, Daniel Guldenring and James McLaughlin
Aims: This study aimed to address the problems faced by clinicians reading and interpreting electrocardiograms (ECGs). Research into ECG interpretation methods and on-line ECG databases were conducted with a view to creating a web based intuitive query builder and decision support tool that would assist diagnostic decision making. Methods: A dataset constructed from on-line ECG library databases was used to create an open source MySQL database of 38 ECG features (e.g. QRS interval, ST amplitude etc. for each lead where appropriate). The Bootstrap framework together with (PHP, HTML) and JavaScript code was used to create a web application. Bootstrap’s responsive design enabled the web application to be used across heterogeneous devices (PC desktop/tablet/mobile phone). Controls were created to allow clinicians to intuitively build queries to search the database. The SELECT fields and a dynamic table control for the WHERE criteria were developed. WHERE criteria were specified in a new table row and consisted of drop down controls and text boxes to speed up data entry. A Run Query button enabled query execution and returned the result-set (diagnoses) in a drop down control. Additional ECG details were displayed in HTML tables consisting of features, causes and background information together with an example ECG image for suggested diagnoses. Results: Queries were easily created and diagnoses were promptly returned within milliseconds. Choosing a diagnosis returned further details within milliseconds that assisted in speeding up the decision making. Conclusion: Modern web development and database technologies provided a user-friendly means of querying an ECG database to assist in the diagnostic decision making process. No SQL knowledge is required by the clinician to build and execute the query. The web application was successful across a number of devices and operated within acceptable response times which has the potential to expedite and improve the decision making process.
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Optimization of Organ Conductivity for the Forward Problem of Electrocardiography
Laura Bear*, Remi Dubois and Nejib Zemzemi
Aims: The relationship defined between epicardial and torso potentials is fundamental to the inverse problem, and is influenced by the organ conductivities within. Here we present a proof of concept for an empirical approach to define these conductivities. Methods: Epicardial potentials were recorded in a closed-chest pig during ventricular pacing. Post-mortem MRI were used to localize electrodes and construct a finite element model, including lungs (l), fat (f), skeletal muscle (m) and cavity (c) volumes. Torso potentials (UT) at 180 “electrodes” were computed from the measured epicardial potentials using conductivities sl=0.05, sf=0.04, sm=0.40, sc=0.22 mSmm-1. For the optimization problem, torso potentials were computed using initial conductivities of sl=sm=sc=0.3 mSmm-1, while sf was kept constant. Optimal conductivities were estimated by minimizing the relative error (RE) between forward computed potentials and UT using a standard gradient-based approach. The gradient of the cost function was approximated using 1) finite differences over electrodes (GradFD), and 2) an adjoint method over mesh nodes (Gradadj). Sensitivity of optimizing conductivities was tested by varying levels of torso electrode location error and Gaussian noise on UT. Results: All conductivities were accurately estimated (<10% difference in value) with up to 1.28 and 0.64cm electrode error, and for up to 0.51 and 0.02uV noise for GradFD and Gradadj respectively. RE increased linearly with increasing electrode error (R2=0.964,0.989) and signal noise (R2=0.997,0.993) for GradFD and Gradadj respectively, with little difference (0-5%) between the methods. Gradadj took <20 iterations for all error levels, while GradFD took 70-90 iterations. Conclusion: Given experimental data with simultaneous epicardial and torso recordings, conductivity within the torso could be accurately estimated. While Gradadj is more computationally efficient, the GradFD is more robust to any noise in the data. Optimizing conductivities would provide not only a more accurate forward model, but also potentially more robust inverse solutions.
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Detection of Incomplete Left Bundle Branch Block by Noninvasive Electrocardiographic Imaging
Laura Bear*, Ruben Coronel, Peter Huntjens, Olivier Bernus, Corentin Dallet, Richard Walton and Remi Dubois
Aims: While complete left bundle branch block (LBBB) can be easily identified in a 12-lead ECG, incomplete LBBB often goes undetected. Non-invasive electrocardiographic imaging (ECGi) may support diagnosis in these cases. This study sought to use a novel ex-vivo porcine model of incomplete LBBB in an experimental torso-tank set up to evaluate ECGi for LBBB detection. Methods: LBBB was induced in Langendorff-perfused pig hearts by radio frequency ablation (n=3) or ligation (n=3) of parts of the left bundle branch. A flexible electrode sock was placed over the epicardium to record 108 electrograms. The level of electrical dyssynchrony was compared to baseline recordings using: 1) The total duration of activation (TAT) and 2) the ventricular electrical uncoupling (VEU), that is the mean LVAT minus the mean RVAT. Five of the hearts were suspended in the human anatomical position in a man-shaped torso-tank filled with Tyrode’s solution and fitted with 256 surface electrodes. Epicardial and surface potentials were recorded during sinus rhythm. Post-experiment MRI provided the epicardial geometry and electrode (epicardial and surface) locations. Epicardial electrograms were calculated using the method of fundamental solutions and Tikhonov regularization, and the derived reconstructed values for electrical dysynchrony were compared to those obtained directly from recorded electrograms. Results: Ablation established complete LBBB in one heart (VEUpre-ablation=0 ms,VEUpost-ablation=49 ms with a 47 ms increase in TAT), was ineffective in 2 (VEUpost-ablation=-3,8 ms). Incomplete LBBB was accomplished in the remaining 3 hearts (VEUpost-ligation=21-24 ms, 7-34 ms increase in TAT). ECGi correctly identified the presence/absence of dyssynchronous activity in 4/5 cases analyzed. Overall, there was no significant difference in VEU (R2=0.86,p=0.42), or TAT values (R2=0.53,p=0.08) between calculated and measured electrograms. Conclusion: ECGi reliably identifies dyssynchronous activation including incomplete LBBB, also without increased TAT. Our results are relevant for fine tuning of resynchronization therapy.
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Reduced QT Variability and increased QT/RR slope in ECG signals of Depressed Patients with Suicidal Ideation
Ahsan Khandoker*, Veena Luthra, Yousef Abouallaban, Muhammad Hasan, Nayeefa Chowdhury and Herbert Jelinek
Major depressive disorder (MDD) is associated with a number of comorbidities including cardiovascular disease (CVD), with an increased risk of death after myocardial infarction. Globally, suicidal behaviour is the third most common cause of death among depressed patients (fifteen precent of depressed patients die by suicide). However, its biological understandings of the phenomena remain ill-defined. The aim of this study was to investigate if parameters for ventricular repolarization variability and dynamics in ECG signals are different in MDD patients with/without suicidal ideation and healthy volunteers. Sixty-one ECG recordings (10 minutes) were acquired and analysed from control subjects (44 CONT), 20 MDD subjects with (MDDSI+) and 21 without suicidal ideation [SI] (MDDSI-) for a case-control analysis at a psychiatric clinic in the UAE. Diagnoses of MDD were made by the Mini-International Neuropsychiatric Interview (MINI) and the severity was assessed using the Hamilton Depression Rating Scale (HAM-D). The subscale for SI consists of 19 items, which was used to evaluate the patients’ suicidal intensions [0 to 38]. Then heart rate-corrected QT interval (QTc) (by following the Bazett’s formula), QT/RR slope [from QT = a[RR] + ß; where a is the slope and ß is the y-intercept], QT variability (QTV) [from standard deviation of QT intervals], QT variability index (QTVI) [ by using QTVI = ?log?_10 [?QT?_v/?QT?_m^2)/(?RR?_v/?RR?_m^ ^2)], Median T wave amplitudes and Twave variability [from standard deviation of T-wave amplitude]. Results are summarized in Table 1. MDD patients with suicidal ideation displayed increased QT/RR slope and reduced QT variability, which may reflect abnormal ventricular repolarization liability and lead to higher risk of cardiac arrhythmia and future cardiovascular diseases. These findings could assist in identifying patients with suicidal ideation in order to provide effective treatment by restoring ventricular repolarization dynamics of MDD patients with suicidal ideation and decrease risk of fatal arhythmia.
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Respiratory Rate Estimation from Multilead ECG Delineation using VCG Directions on Fiducial Points
Maikel Noriega, Ennis Carcases, K Duran, Enrique Marañón, Juan Pablo Martínez* and Rute Almeida
Introduction: Estimating the instantaneous respiratory rate (Rr) from the electrocardiogram (ECG) is of interest as respiration direct measurement in clinical situations is often cumbersome. Several studies have developed signal processing techniques to extract respiratory information from the modulation of the ECG morphology. However, the single lead R-peak amplitudes (RPA) was shown not to yield accurate Rr estimates, which is in part because the suitability of a given ECG lead to represent the respiratory influence is subject dependent. For this reason, the Rr estimation from ECG with multi lead algorithm becomes more important. Methods: In this study, the Rr was estimated from the beat-to-beat series of "Final Directions" (FD) obtained in a previously proposed multilead ECG delineator. Those FD are obtained as those presenting maximal projection of the wavelet-transform loop for QRS complex main peak (Rp), T wave peak (Tp) and T wave end (Te). The series are subject to power espectral analysis to estimate Rr. To validate the proposed algorithm, a control database (40 subjects, 12 leads) recorded at University of Zaragoza was considered. The Frank leads were synthesized using the inverse Dower transformation. Additionally, Rr was estimated from the single lead RPA series. Results: The average of mean absolute error (MAE) across files in terms of breaths-per-minute was 2.99, 3.03 and 3.01 for estimates from the FD series of QRS complex main peak and T wave peak and end, respectively. The average MAE of single lead RPA estimates was between 3.30 bpm (lead V4) and 5.22 bpm (lead aVF). Conclusions: The proposed strategy based final direction of maximum projection outperform the best results obtained from the single lead RPA series, representing an alternative for Rr estimation. Additionally, the beat-to-beat estimation of Rr can be obtained as an extra output of multilead delineation with almost no extra effort.
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Comparison of Four Recovery Algorithms Used in Compressed Sensing for ECG Signal Processing
Zhimin Zhang*, Shoushui Wei, Dingwen Wei, Liping Li, Feng Liu and Chengyu Liu
Background: Compressed Sensing (CS) has been widely used for ECG signal processing with the rapid development of real-time dynamic ECG applications. Reconstruction process is essential in CS and many recovery algorithms were reported in the last decades. However, the comparative study for the performances of different recovery algorithms for CS-based ECG signal processing lacks, especially for the real-time applications. This study aimed to investigate these issues and provide useful information. Methods: Thirty-six 10-s ECG recordings from MIT-BIH Normal Sinus Rhythm Database were used for the CS analysis. All ECG data were firstly compressed using a Gaussian random matrix and then were reconstructed by four typical recovery algorithms, i.e., compressed sampling matching pursuit (CSMP), orthogonal matching pursuit (OMP), expectation-maximum-based block sparse Bayesian learning (BSBL_EM) and bound-optimization-based block sparse Bayesian learning (BSBL_BO). The evaluation criterion for a successful recovery was that the percentage of root-mean-square difference (PRD) was less than 9%. PRD, as well as compression ratio (CR) and reconstructing time (RT), were calculated. Each recovery algorithm was executed for 100 times for each recording, for the purpose of removing the influence of random factor in the compression matrix. Results: The results of evaluation indices for CSMP method were PRD=8.02%, CR=69.44% and RT=8.7 s, for OMP methods were PRD=8.99%, CR=57.78% and RT=2.2 s, for BSBL_EM method were PRD=8.75%, CR=41.11% and RT=1.3 s, and for BSBL_BO method were PRD=8.41%, CR=31.11% and RT=1.5 s. Conclusion: With the setting of PRD<9%, among the four recovery algorithms, BSBL_BO method had the best compression ratio while BSBL_EM achieved the shortest reconstructing time. By contrast, CSMP method had the worst compression ratio. Meanwhile, the long running time of 8.7 s in CSMP for 10-s ECG analysis indicated that it was not suitable for real-time applications.
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Myocardial Ischemia Events Detection based on Support Vector Machines using QRS and ST Features
Rudys Magrans, Pedro Gomis* and Pere Caminal
Introduction: ST-segment deviation and QRS-derived indices have been individually used to detect acute myocardial ischemia. The aim of this study was developing a nonlinear (Gaussian kernel) support vector machine (SVM) model to detect ischemic events based on a dataset of QRS-derived and ST indices from non-ischemic and acute ischemic episodes. Methods: Sixty-seven patients who underwent elective percutaneous coronary intervention (PCI) with balloon inflation periods of mean 4.7 minutes were studied. Twelve lead continuous ECG before and during PCI were obtained and signal-averaged. Fifty-four indices were initially considered from each episode. The dataset was randomly divided into training (80%) and testing (20%) subsets. A pre-filtering stage was applied on the training subset to select only statistically significant changing indices between both episodes. Then the training subset was used to optimize the SVM parameters algorithm and for determining the most important statistically significant indices, by using k-fold cross-validation (k=5). Cross-validation procedure was repeated 25 times to quantify the variation of predictions from different splits of the subset on training. The final model was constructed using the total training subset for optimal combination of parameters and indices, and assessed by means of the testing subset. The whole procedure was run on 25 randomized training/testing subsets to assess the average performance. Results: On average, the most important indices were the QRS-vector difference and the ST segment level at J-point + 60 ms computed from the synthesized vector magnitude, and the summed high-frequency QRS components of all 12 leads at 150 – 250 Hz band. The performance of testing was: classification error = 12.5(8.3-16.7)%, sensibility = 83.3(75.0-91.7)%, specificity = 91.7(83.3-91.7)%, positive predictive value = 90.9(83.0-92.3)% and negative predictive value = 85.7(80.0-91.7)%. Conclusions: The method used to construct the SVM model is robust enough and looks promising in detecting acute myocardial ischemia and myocardial infarction risk.
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Response of Ventricular Repolarization Parameters to Preload Changes in Isolated Working Heart
Jakub Hejc*, Oto Janousek, Marina Ronzhina, Tibor Stracina, Veronika Olejnickova, Jana Kolarova and Marie Novakova
Aim: Heart rate dependency of ventricular repolarization (VR) parameters is well known phenomenon since many years ago. Other factors that can contribute to VR regulation are still under investigation. One of possible control mechanism is so-called mechano-electric coupling; electrophysiology changes induced by mechanical stretch. We investigate step response of VR parameters to abrupt changes in mechanical end-diastolic load. Methods: Ten New Zealand white rabbit hearts were isolated and perfused in working heart mode. Each heart was kept at constant heart rate by permanent left atrial pacing. Changes in preload were induced by abrupt increase in perfusion apparatus water column level in range of 8–11 cmH2O within step of 1, 2 and 3 cmH2O. Electrical activity was recorded at sampling frequency 10 kHz by seven non-contact unipolar leads equally positioned around left ventricle in range of angles from 0° to 180°. To obtain global view on ventricular repolarization, singular value decomposition was used to reconstruct one global lead in which four VR parameters (QT, QTPeak, RT and RTPeak) were detected by custom made algorithm. Results: Response of VR parameters to mechanical load is highly subject specific including non-responders or non-detectable changes due to low rate of increase in preload or signal to noise ratio of delineated intervals. On this account, RT and RTPeak are less sensitive to delineation errors and thus more reliable for an analysis. In responding subjects, step response of VR parameters has three different phases: (1) gradual prolongation up to 2–5 ms; (2) temporarily stable state and (3) slow adaptation back to baseline value. Total time of the process reaches up to 40–50 seconds.
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Dynamic Coupling Between Ventricular Repolarization Duration and RR-Interval Phase-Rectification Analysis in Chagas Disease
Paulo Roberto Benchimol-Barbosa*, Olivassé Nasario-Junior, Jurandir Nadal and Roberto Coury Pedrosa
Dynamic ventricular repolarization duration (VRD) vs. RR-interval coupling relates to tachyarrhythmia vulnerability, particularly in chronic Chagas dis-ease (ChD). Phase-rectification of RR-interval series separates acceleration (AC) and deceleration (DC) phases (Figure 1), reflecting sympathetic and parasympathetic influences on heart rate, respectively. This study investigat-ed VRD and phase-rectification-driven RR-interval coupling to assess dy-namic repolarization adaptation in healthy and chronic ChD subjects. Healthy sedentary (Control, n=11) and ChD (n=11) groups were studied. All were in sinus rhythm and underwent 60 min head-up tilt table test. ChD group were submitted to MIBG scintigraphy to assess cardiac sympathetic innervation. Histogram of RR-interval series was calculated, with 100 ms class, ranging from 600 ms to 1200 ms. For each class, mean of normal RR-intervals (MRR) and mean of the peak-to-peak R-to-T wave interval (MRT), representing VRD, were calculated and analyzed in the whole series (T), and in DC and AC phases. Linear regression model of MRT vs. MRR were com-puted for each group, and respective slopes calculated (sMRT-T, sMRT-DC and sMRT-AC). Correlation coefficients were tested before analysis, and Student t-test compared groups (a<0.05). MRT-T, MRT-AC and MRT-DC significantly increased as a function of MRR in all groups, and slopes were significantly different between groups in phase-matched comparisons (Table 1). All ChD subjects presented reduced cardiac MIBG uptake. In a linear model of VRD RR-interval coupling, average RT-interval increases as a function of RR-interval, in both ChD and healthy subjects during tilt-table test. However, in ChD subjects showing sympathetic denervation, average RT-interval is long-er and exhibited a flatter slope in a linear RR-interval coupling model. Table 1 – Slopes of MRT vs. MRR regression lines and intervals duration per group (mean ± SD): Group sMRT-T sMRT-DC sMRT-AC MRR(ms) MRT(ms) Control 0.156±0.005* 0.161±0.007* 0.158±0.005* 806±72.4 265±11.6 ChD 0.115±0.009* 0.110±0.010* 0.132±0.002* 906±51.6 273±10.6 *p<0.05 intergroup comparison
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Automatic Detection of the Wolff-Parkinson-White (WPW) Syndrome from Electrocardiograms (ECGs)
Hassan Adam MAHAMAT*, Sabir Jacquir, Cliff Khalil, Gabriel Laurent and Stéphane Binczak
The Wolff-Parkinson-White (WPW) syndrome is a cardiac conduction trouble associated with reentry tachycardia and may even be responsible for sudden cardiac death. This congenital abnormality corresponds to a “short circuit” between atria and ventricles due to the presence of an accessory pathway (AP). In Europe, the prevalence of the WPW syndrome is about 0.15 to 0.31%, it is the second most common cause of paroxysmal supraventricular tachycardia. When patent, the WPW syndrome can be diagnosed on a 12-lead standard ECG as it usually produces a PR interval, a prolonged QRS duration due to the presence of a so called delta wave. Aside from medical anti-arrhythmic drugs, the main treatment is based on the physical eradication of the AP by applying radiofrequency energy with a dedicated lead on its precise location by endovascular techniques. To date its precise location around tricuspid or mitral annulus is based on non-practical algorithms that have been published over the years. Those methods are mainly based on the identification of delta wave morphologies on 12 lead-ECGs. We have developed a completely new method based on the whole complex QRS morphology analysis as opposed to previous algorithms based on delta wave patterns only. Therefore we have used the continuous wavelet transform, the detection of P waves, QRS complexes and T waves. Duration of those waves has been computed after determination of the boundary location (onset and offset of the P, QRS and T waves). Based on the whole QRS complex upstroke and morphology the analysis has been performed on 12 lead-ECGs of patients who have been efficiently treated by endovascular techniques. This new automated algorithm has been tested on the physionet Ptbdb database in order to confirm its robustness. This method should help physicians in their daily clinical practice.
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Classification of Multiform Ventricular Extrasystole Using Morphology Match over the Reconstructed Phase Space of Electrocardiogram
Hsiao-Lung Chan*, Chun-Li Wang, Shih-Chin Fang and Yi-Sheng Lee
Ectopic electrical activity in the ventricle usually causes an extrasystole, typically as a premature ventricular contraction (PVC). The presence of multiform PVC reflects complex electrocardiographic abnormality. Patients with multiform PVC were shown to have a higher incidence of adverse event than patients with uniform PVC. In addition, the mortality rate in the multiform group was also higher compared to the uniform group. Therefore, characterization of multiform PVC is beneficial for prognosis of cardiovascular disease whereas classification of multiform PVC is an essential procedure for the characterization. Here, we propose a new morphology matching of heartbeats over the reconstructed 3-dimensional phase space from single-lead electrocardiogram. A similarity measure, the spatial correlation (SC) is defined as the incident rate of phase space trajectories on the divided M×M×M cube. Another dissimilarity measure, the mutual nearest point distance (MNPD) is obtained by calculating point-to-nearest-point distances between two phase space trajectories. An unsupervised heartbeat classification is developed based on cluster separation and cluster merging using similarity or dissimilarity measure. The assessment based on the MIT/BIH arrhythmia database demonstrated the classification based on MNPD had higher accuracies in distinguishing PVC from normal heartbeats and separating PVC with different morphology compared to that based on the SC.
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Auto-Cropping of Phone Camera Color Images to Segment Cardiac Signals in ECG Printouts
Fernando Lozano-Fernández*, Inmaculada Mora-Jiménez, Margarita Sanromán-Junquera, Sergio Muñoz-Romero, Arcadio García-Alberola and Jose Luis Rojo-Alvarez
Digital analysis of the bio-electrical signals allows us to obtain valuable information for clinical and research purposes. Despite current devices record and store the digital signal, in some cases only a printout version is available. Previous scientific research has proposed algorithms to digitize the printed signal from a scanned image. Nowadays, it is possible to obtain an image of the printouts by just taking a color photograph with the digital camera of a cell phone. Most of the current algorithms to digitize the signals start from images containing just one signal, which is manually selected. We propose a procedure to automatically crop the image as many sub-images as signals in the printout. Then, different signal extraction methods available in the literature can be used to digitize every individual signal. We particularize our procedure for ECG printouts. A preprocessing stage is required to correct the perspective and prepare the image for the auto-cropping procedure. After perspective correction, chromatic components are extracted in the YCbCr color space. The Cr component is selected for red grids. For other colored grids, a new image is obtained from the relative color difference. This image, I, mainly contains the grid. The grayscale image, G, and I are both processed with morphological operators to emphasize both signal and grid in G, and grid in I. Both images are subtracted and the horizontal projection is computed. Boundaries among contiguous signals are found by applying morphological operators such as closing, reconstruction and maxima extinction filters to the projection. These boundaries are used to obtain the sub-image associated to each signal. Thirty phone camera color images of continuous and discontinuous grid ECG printouts were used for evaluation. Images were taken from a distance of 15cm to cover 3 leads. Our procedure worked correctly when consecutive lead sub-images were not overlapped.
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Do we need to enforce the homogeneous Neumann condition on the torso for solving the inverse electrographic problem?
Judit Chamorro-Servent*, Laura Bear, Josselin Duchateau, Mark Potse, Remi Dubois and Yves Coudière
INTRODUCTION: Robust representation of the forward problem of non-invasive electrocardiographic imaging (ECGI) may require accurate specification of boundary conditions at the torso and cardiac surfaces. In the method of fundamental solutions (MFS), the potentials are expressed as a linear combination of fundamental solutions of Laplace’s equation over a discrete set of virtual sources placed outside the domain of interest. An objective function allows the determination of the solution that better approximates the Dirichlet and homogeneous Neumann conditions (HNC) at the torso surface. HNC requires accurate computation of normal directions at torso electrodes positions and Laplace fundamental solution derivatives. However, we hypothesize that these derivatives at torso locations are inherently close to zero, and the cost and difficulty to compute HNC is negligible. METHODS: First, for a simulated data set built with complex three-dimensional models of propagation of electrical activity, we studied the effect of weighting the MFS objective function in consideration of the Dirichlet and Neumann conditions respectively, and compared it to standard MFS (where both conditions are equally weighted). Afterwards, we reconstructed epicardial potentials for five activation sequences, using the standard MFS and the MFS without HNC (both by zero-order Tikhonov and CRESO regularization parameter). Finally, we compared the electrograms and activation times to the reference epicardial signals. RESULTS: A small ratio between the norms of the HNC part of the MFS matrix and its respective Dirichlet part was found (~10-2-10-3), indicating the negligibility of the HNC. Reconstructed electrograms not including HNC had significantly higher CCs (p<0.0001), and lower REs (p<0.0001) than including them. Activation times not including HNC results showed CCs ~0.002 to 0.004 greater (p<0.001), and RE values 1.6-1.9% lower (p<0.0001). CONCLUSION: We provide results showing the negligibility of HNC for the MFS problem. This finding reduces the computational burden to solve the forward and inverse problem.
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Empirical Mode Decomposition Template Matched Filter for Detection and Estimation of T-Wave Alternans
Asim Bakhshi, Muhammad Latif, Sajid Bashir and Hafiz Munsub Ali*
Introduction: T-wave alternans (TWA) is a well recognized marker for sudden cardiac death. It involves beat-to-beat periodic variations in amplitude of ECG ST-T complexes, showing stationary as well as non-stationary temporal characteristics. TWA analysis becomes a challenge under the presence of process noises, transient outliers and physiological artifacts. Targeting detection of distributed alternant energy rather than peak amplitude, we propose a template matched filter based detection theoretic approach (EMF). Empirical Mode Decomposition (EMD) is used for alternant waveform trend estimation to construct the matched-filter template. Unlike classical implementations in a similar context, the varying nature of the constructed template better estimates the non-stationary and transient TWA episodes. Methods: After QRS and T-wave delineation, even and odd ST-T complexes are segregated. For each even-odd pair, the difference being the alternant waveform is matched against a corresponding dynamically generated template through decomposition into intrinsic mode functions and subsequent reconstruction. Finite impulse response implementation of the classical energy detector maximizes SNR at the output, providing the required energy estimate. Generalized likelihood ratio decision statistic, obtained using receiver operating characteristics curves, is used for TWA detection test. Results: Proposed detector outperforms correlation method (CM) and static median template based matched filter for complete range of SNR (-15 to 30 dB) and all noise types. Attained performance is also comparable to spectral method (SM) and its EMD based improvement (EMD-SM) for electrode and motion artifacts. Estimation bias of EMF approaches that of SM for SNR = 20 dB and remains better than MMAM throughout. Observed relative bias of EMF approaches SM for alternans magnitude > 20 µV with both real noise types. Efficacy of EMF is vindicated for dynamic TWA tracking where it is compared against other detectors under variety of TWA episodes.
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Is There Any Association Between Ventricular Ectopy and Falls in Community-dwelling Older Adults?
Saman Parvaneh*, Bijan Najafi, Nima Toosizadeh, Irbaz Bin Riaz and Jane Mohler
Background: Falls are common in older adults, one in three older adults age 65 years and older falls every year. Over 700,000 US patients a year are hospitalized after a fall, most often due to a head injury or hip fracture. Dizziness is one of factors that is associated with higher risk of falling. Frequent ventricular ectopic (Premature Ventricular Contraction, PVC) beats can cause dizziness due to the reduced ability of the heart to pump blood in systemic circulation. Therefore, the main goal of this study was to study the prevalence of PVC in community-dwelling older adults with, and without, history of falling. Method: A four hour uni-channel ECG was recorded using an FDA-approved wearable-sensor in 45 elders aged 65 and above. Participants were categorized as non-fallers (n=22) and fallers (n=23) based on historical report of falling in the last 12 month. The number of self-reported falls ranged from zero and six. For data analysis, PVC beats were extracted using a Matlab code, and reviewed by an expert to ensure accuracy. Number of PVCs per hour was extracted as the parameter of interest in this study and compared between fallers and non-fallers using independent sample t-test with p= 0.05 as statistically significant level. Results: Number of PVC beats was not significantly different (p>0.05) between non-fallers (41.65±74.22) and fallers (43.62±59.48). When the number of PVCs was compared between non-fallers and fallers with just one fall an increasing trend in prevalence of PVC was observed (non-fallers: n=22, PVC=(41.65±74.22); fallers with one fall: n=13, PVC=63.15±73.69). Discussion: In this study, no relationship between prevalence of PVC and falls was found. A high standard deviation in PVC was observed in the studied population, and may be associated with the wide diversity of participants.
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Classification Methodology of CVD with Localized Features Analysis Using Phase Space Reconstruction Targeting Personalized Remote Health Monitoring
Naresh Vemishetty, Amit Acharyya, Saptarshi Das, Shivteja Ayyagari, Soumya Jana*, Koushik Maharatna and Paolo Emilio Puddu
According to the survey conducted by WHO, CVDs are the primary drivers for the high mortality rate all over the world among all the non-communicable diseases. To detect, monitor and diagnose CVD remotely in personalized manner, affordable and reliable devices for remote health care monitoring devices need to be developed that would classify even the minute abnormalities of the heart apriori. Accounting this, we propose here a real-time CVD classification methodology based on the localized features analysis of individual ECG-PQRST complexes using Phase Space Reconstruction (PSR) technique. Recently, PSR technique has shown prospect of offline-detection of Ventricular Arrhythmias when analyzed statistically on large dataset of many samples. However, the existing PSR technique works on several stored PQRST complexes,the classification of CVD would not be accurate in fragmented QRS complexes or ECG in absent of P wave or any small desynchronization in the individual ECG beats due to missing of some important and interesting diagnostic features. Therefore the proposed classification methodology uses the localized features (QRS interval,PR interval) of individual ECG beats from our already proposed Feature Extraction (FE) block(Fig.1) and detect the desynchronization in the given intervals after applying the PSR technique. Considering the QRS interval, if any notch is present in the QRS complex, then the corresponding contour(Fig.2) will be appear and give the variation in the box count indicating a notch in the QRS complex. Likewise, the contour and the disparity of box count due to the variation in the PR and ST interval localized wave have been noticed using the proposed PSR technique. MIT-BIH and PTBDB database has been used to verify the proposed CVD methodology on various abnormalities like fragmented QRS complexes,myocardial infarction, Hyperkalemia and atrial fibrillation. The design have been successfully tested for diagnosing various disorders with 98% accuracy on all the specified abnormal databases.
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Adaptive Modulation Spectral Filtering for Improved Electrocardiogram Quality Enhancement
Diana Tobon* and Tiago Falk
Advances in wearable electrocardiogram (ECG) monitoring devices has allowed for new cardiovascular applications to emerge beyond diagnostics, such as stress detection, sleep disorder characterization, mood recognition, activity surveillance, or fitness monitoring, to name a few. Such devices, however, are prone to artifacts, particularly due to movement, thus rendering heart rate and heart rate variability metrics useless. To address this issue, this paper proposes a new ECG quality enhancement algorithm based on filtering in the so-called spectro-temporal domain. That domain characterizes the rate-of-change of ECG spectral components, which differ from artifacts components. Our experiments show that this new signal representation accurately separates ECG signal and noise components, thus allowing for adaptive filtering to improve signal quality even in extremely noisy settings. For testing, we used synthetic signals with heart rates between 50 and 180 bpm to cover tachycardia, bradycardia, and different activity levels such as sitting, walking, and running. Also, low frequency to high frequency ratio was randomly sampled between 0.5 and 8.9 to cover light-to-deep sleep, wakefulness, myocardial infarction, and rapid eye movement. The synthetic signals were contaminated with artifacts taken from MIT-BIH Noise Stress Test Database at five different signal-to-noise (SNR) levels (i.e., -10, -8, -5, 0, and 5 dB). Experimental results show the proposed algorithm outperforming a state-of-the-art wavelet-based enhancement algorithm in terms of SNR ratio improvement, as well as ECG kurtosis. We found an average SNR improvement for noisier signals of 9 dB compared to 4 dB with the benchmark. Further, an average kurtosis increase over the noisy signal of 4 was obtained, thus outperforming the subtle increase of 0.1 obtained with the benchmark. These findings suggest that the proposed algorithm can be used to enhance the quality of wearable ECG monitors even in extreme conditions, thus can play a key role in athletic peak performance training/monitoring.
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Automatic Location of Sources of Electrical Activation from Electroanatomical Maps
Fernando Barber, Miguel Lozano, Ignacio Garcia-Fernandez and Rafael Sebastian*
Motivation: The activation of the myocardial muscle is triggered by Purkinje-myocardial junctions (PMJs), which are the terminal sites of the specialised cardiac conduction system (CCS). The CCS coordinates and dictates the sequence of activation in the ventricles, and can be interfered by ectopic activity or late activated areas triggered by slow conduction channels. Obtaining the location of the PMJs and other sources of endocardial ectopic activity would be desirable for build computer models of cardiac electrophysiology and planning ablation interventions. Aims: This study aims to estimate the location and activation time of all relevant endocardial sources of electrical activity from a discrete set of endocardial measurements obtained by an electro-anatomical mapping system (EPM). Given the proportion of EPM samples versus trigger points the system will locate trigger points with an error in the order millimetres. Methods: From the set of EPM samples (location and time) a Delaunay triangulation is used to create an annotated mesh. Considering a constant circular propagation velocity on myocardial tissue a solver is used to determine the theoretical source of activation of each triangle. After processing all the triangles, the sources that activate at least two tringles are considered true sources. The residual triangles point out areas whose source cannot be determined due to low mapping density. Synthetic CCS with different branching pattern and PMJ density were built (see figure 1, left) to generate activation maps. Results: Activation maps were sampled at random locations (see crosses in Figure 1, right) with increasing density to evaluate the number of real sources detected. The percentage of sources recovered depended their area of influence and inter-spacing, since in clustered configurations (figure 1, left C) sensed locations inside the cluster were too few. When right spacing and proportion of sources/sensors was reached, the exact location of PMJs was obtained.
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