Sensitivity Analysis and Parameter Identification of a Cardiovascular Model in Aortic Stenosis

Marion Taconné1, Virginie Le Rolle2, Kimi Owashi3, Vasileios Panis4, Arnaud Hubert4, Vincent Auffret4, Elena Galli3, Alfredo Hernandez5, erwan donal6
1LTSI INSERM, 2LTSI - INSERM U1099 - Université de Rennes 1, 3Univ Rennes, CHU Rennes, Inserm, LTSI – UMR 1099, F-35000 Rennes, France, 4CHU Rennes, 5INSERM - LTSI U 1099, 6LTSI UNiversité Rennes-1


Context: Aortic stenosis (AS) is a narrowing of the aortic valve opening. Although left ventricular (LV) pressure curve is essential for the estimation of myocardial work indices (Owashi, 2020), its estimation remains difficult in AS. The objective of this study is to propose a model-based method, adapted to patients with AS, in order to reproduce LV pressure and volume from clinical invasive and non-invasive data.

Methods: The model of the cardiovascular system (CVS) is composed of i) cardiac electrical activity, ii) elastance-based mechanical activity, iii) systemic and pulmonary circulations and iv) heart valves. A sensitivity analysis of the proposed model was performed using the Morris elementary effects method (Morris, 1991) on stroke volume (SV) and transaortic pressure gradient (∆P). Then, a patient-specific parameter identification was implemented with evolutionary algorithms on experimental LV pressure curve, volume curve, systolic and diastolic arterial pressures. The experimental dataset includes echocardiography and invasive pressures measured from 3 patients with severe aortic stenosis.

Results: The sensitivity analyses were applied on 80 parameters with ranges selected from previous work and literature ± 30%. The most influent parameters on ∆P were mainly related to the aortic valve, whereas most important parameters on SV are associated with LV systolic and diastolic properties. The parameters with the highest sensitivities were selected for parameter estimations. A close match was observed between experimental and simulated pressure and volume curves. The global root mean square error (RMSE) for pressure and volume curves are respectively 21.8 (±1.8) mmHg and 14.8 (±9.4) ml.

Conclusions: The model-based approach proposed shows promising results to generate accurate LV pressure in AS case. Further work will focus on patient specific identification in non-invasive data and integrate in the assessment of myocardial work.