Personalized evaluation of the passive myocardium in ischemic cardiomyopathy via computational modeling using Bayesian optimization.

Autor: Torbati S; Research Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.; School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran., Daneshmehr A; School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran., Pouraliakbar H; Rajaie Cardiovascular, Medical, and Research Center, Iran University of Medical Sciences, Tehran, Iran., Asgharian M; Department of Mathematics and Statistics, McGill University, Montreal, QC, Canada., Ahmadi Tafti SH; Research Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran. ahmadita@tums.ac.ir.; Department of Surgery, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran. ahmadita@tums.ac.ir., Shum-Tim D; Division of Cardiac Surgery, Department of Surgery, McGill University, Montreal, QC, Canada., Heidari A; Department of Mathematics and Statistics, McGill University, Montreal, QC, Canada. alireza.heidari@mcgill.ca.; Department of Mechanical Engineering, McGill University, Montreal, QC, Canada. alireza.heidari@mcgill.ca.; Department of Biomedical Engineering, McGill University, Montreal, QC, Canada. alireza.heidari@mcgill.ca.
Jazyk: angličtina
Zdroj: Biomechanics and modeling in mechanobiology [Biomech Model Mechanobiol] 2024 Oct; Vol. 23 (5), pp. 1591-1606. Date of Electronic Publication: 2024 Jul 02.
DOI: 10.1007/s10237-024-01856-0
Abstrakt: Biomechanics-based patient-specific modeling is a promising approach that has proved invaluable for its clinical potential to assess the adversities caused by ischemic heart disease (IHD). In the present study, we propose a framework to find the passive material properties of the myocardium and the unloaded shape of cardiac ventricles simultaneously in patients diagnosed with ischemic cardiomyopathy (ICM). This was achieved by minimizing the difference between the simulated and the target end-diastolic pressure-volume relationships (EDPVRs) using black-box Bayesian optimization, based on the finite element analysis (FEA). End-diastolic (ED) biventricular geometry and the location of the ischemia were determined from cardiac magnetic resonance (CMR) imaging. We employed our pipeline to model the cardiac ventricles of three patients aged between 57 and 66 years, with and without the inclusion of valves. An excellent agreement between the simulated and the target EDPVRs has been reached. Our results revealed that the incorporation of valvular springs typically leads to lower hyperelastic parameters for both healthy and ischemic myocardium, as well as a higher fiber Green strain in the viable regions compared to models without valvular stiffness. Furthermore, the addition of valve-related effects did not result in significant changes in myofiber stress after optimization. We concluded that more accurate results could be obtained when cardiac valves were considered in modeling ventricles. The present novel and practical methodology paves the way for developing digital twins of ischemic cardiac ventricles, providing a non-invasive assessment for designing optimal personalized therapies in precision medicine.
(© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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