Literature DB >> 31294752

Method for Calibration of Left Ventricle Material Properties using 3D Echocardiography Endocardial Strains.

Yaghoub Dabiri1, Kevin Sack2, Nuno Rebelo3, Peter Wang4, Yunjie Wang5, Jenny Choy6, Ghassan S Kassab7, Julius Guccione8.   

Abstract

We sought to calibrate mechanical properties of left ventricle (LV) based on 3D speckle tracking echocardiographic imaging data recorded from 16 segments defined by American Heart Association (AHA). The in vivo data were used to create finite element (FE) LV and biventricular (BV) models. The orientation of the fibers in the LV model was rule-based, but diffusion tensor magnetic resonance imaging (DT-MRI) data were used for the fiber directions in the BV model. A nonlinear fiber-reinforced constitutive equation was used to describe the passive behavior of the myocardium, whereas the active tension was described by a model based on tissue contraction (Tmax). Isight was used for optimization, which used Abaqus as the forward solver (Simulia, Providence, USA). The calibration of passive properties based on the end diastolic pressure volume relation (ED PVR) curve resulted in relatively good agreement (mean error = -0.04 ml). The difference between experimental and computational strains decreased after segmental strain metrics, rather than global metrics, were used for calibration: for the LV model, the mean difference reduced from 0.129 to 0.046 (circumferential) and from 0.076 to 0.059 (longitudinal); for the BV model, the mean difference nearly did not change in the circumferential direction (0.061) but reduced in the longitudinal direction from 0.076 to 0.055. The calibration of mechanical properties for myocardium can be improved using segmental strain metrics. The importance of realistic fiber orientation and geometry for modeling of the LV was shown.

Year:  2019        PMID: 31294752     DOI: 10.1115/1.4044215

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  3 in total

Review 1.  Biomechanics of infarcted left ventricle: a review of modelling.

Authors:  Wenguang Li
Journal:  Biomed Eng Lett       Date:  2020-06-10

2.  Application of feed forward and recurrent neural networks in simulation of left ventricular mechanics.

Authors:  Yaghoub Dabiri; Alex Van der Velden; Kevin L Sack; Jenny S Choy; Julius M Guccione; Ghassan S Kassab
Journal:  Sci Rep       Date:  2020-12-18       Impact factor: 4.379

3.  Prediction of Left Ventricular Mechanics Using Machine Learning.

Authors:  Yaghoub Dabiri; Alex Van der Velden; Kevin L Sack; Jenny S Choy; Ghassan S Kassab; Julius M Guccione
Journal:  Front Phys       Date:  2019-09-06
  3 in total

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