Abstract
In this study, we present a computational framework designed to evaluate virtual scenarios of cardiac resynchronization therapy (CRT) and compare their effectiveness based on relevant clinical biomarkers. Our approach involves electro-mechanical numerical simulations personalized, for patients with left bundle branch block, by means of a calibration obtained using data from Electro-Anatomical Mapping System (EAMS) measures acquired by cardiologists during the CRT procedure, as well as ventricular pressures and volumes, both obtained pre-implantation. We validate the calibration by using EAMS data coming from right pacing conditions. Three patients with fibrosis and three without are considered to explore various conditions. Our virtual scenarios consist of personalized numerical experiments, incorporating different positions of the left electrode along reconstructed epicardial veins; different locations of the right electrode; different ventriculo-ventricular delays. The aim is to offer a comprehensive tool capable of optimizing CRT efficiency for individual patients. We provide preliminary answers on optimal electrode placement and delay, by computing some relevant biomarkers such as dP/dtmax , ejection fraction, stroke work. From our numerical experiments, we found that the latest activated segment during sinus rhythm is an effective choice for the non-fibrotic cases for the location of the left electrode. Also, our results showed that the activation of the right electrode before the left one seems to improve the CRT performance for the non-fibrotic cases. Last, we found that the CRT performance seems to improve by positioning the right electrode halfway between the base and the apex. This work is on the line of computational works for the study of CRT and introduces new features in the field, such as the presence of the epicardial veins and the movement of the right electrode. All these studies from the different research groups can in future synergistically flow together in the development of a tool which clinicians could use during the procedure to have quantitative information about the patient's propagation in different scenarios.