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Communication Dans Un Congrès Année : 2020

Patient-Specific Analysis of Myocardial Strains in Left Bundle Branch Block Based on Computational Models

Résumé

This paper proposes a patient-specific model-based estimation of myocardial strain signals and the evaluation of echo-based parameters, adapted to patients with left bundle branch block (LBBB). The left ventricle (LV) was divided into 16 segments in order to evaluate concurrently different regions at the ventricular contraction process. For each LV segment, some parameters, associated with the active and passive components of the cardiac muscle, the electro-mechanical driving function and the electrical depolarization time, were identified using evolutionnary algorithms. The proposed approach was evaluated on data obtained from 3 LBBB patients. From patient-specific simulations, we also analysed electrical activation delay and myofiber contractility in LV segments. A close match was observed between experimental and simulated myocardial strain curves for all the subjects. The root mean square error (RMSE) is equal to 2.87(± 1.00), 2.49(± 0.55) and 3.63(± 0.81) for the anterior ischemic, the lateral ischemic and the non-ischemic LBBB patients, respectively. The proposed patient-specific model-based approach may be a useful tool for understanding LV mechanical dyssynchrony and identifying patients suitable for cardiac resynchronization therapy (CRT). © 2020 Creative Commons; the authors hold their copyright.

Dates et versions

hal-03157780 , version 1 (03-03-2021)

Identifiants

Citer

K.P. Owashi, Elena Galli, A. Hubert, Erwan Donal, A.I. Hernandez, et al.. Patient-Specific Analysis of Myocardial Strains in Left Bundle Branch Block Based on Computational Models. 2020 Computing in Cardiology, CinC 2020, Sep 2020, Rimini, Italy. pp.9344313, ⟨10.22489/CinC.2020.220⟩. ⟨hal-03157780⟩
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