LAUSR

The noninvasive assessment of myocardial work by pressure-strain loops (PSL) analysis is a recently introduced tool to estimate myocardial performance. PSL analysis cannot be applied to patients having an obstacle to LV ejection, as in the case of aortic stenosis (AS), because of the difficulty to estimate left ventricular (LV) pressure. The purpose of this work is to propose a non-invasive model-based estimation of the left ventricular pressure curve in AS patients in order to evaluate myocardial work indices. Twelve patients with moderate-to-severe AS underwent cardiac catheterization to acquire the LV pressure (Pexp-LV). All patients underwent a standard trans-thoracic echocardiography to extract regional myocardial strain curves and estimate the aortic valve area (AVA). Systolic and diastolic arterial pressures were also measured. The proposed cardiovascular system (CVS) model is composed of four main coupled sub-models simulating: i) cardiac electrical activities, ii) cardiac cavity, iii) the systemic and pulmonary circulation, and iv) cardiac valves (Figure 1, upper panel). A 2-step parameter identification strategy, based evolutionary algorithms, was implemented to learn LV parameters from Pexp-LV and to estimate patient-specific model-based LV pressure curves (Pmodel-LV) starting from parameters obtained from non-invasive hemodynamics. Global myocardial constructive work (GCW) and myocardial wasted work (GWW) were calculated using Pexp-LV and Pmodel-LV. A close match was observed between Pexp-LV and Pmodel-LV, with a mean total relative error of 12.27% (range 5.9% to 17.40%). When considering GCW and GWW, global correlation was equal to 0.92 (p<0.0001). In BA analysis, mean bias was −2.9 mmHg.%, which corresponds to relative bias equal to 0.11% with respect to the mean value of work indices (Figure 1, lower panel). A model-based approach can be used to estimate LV pressure and myocardial work indices in patients with AS, and be provide a promising tool for the assessment of myocardial performance in patients with AS Type of funding source: None