A Computational Framework for Atrioventricular Valve Modeling using Open-Source Software

TL;DR

This paper introduces an open-source computational framework combining SlicerHeart and FEBio for image-based biomechanical analysis of atrioventricular valves, aiming to improve valve repair strategies especially in pediatric populations.

Contribution

It develops and verifies an open-source, reproducible platform for modeling atrioventricular valves from medical images, filling a gap left by commercial tools.

Findings

High fidelity in modeling pediatric mitral and tricuspid valves

Excellent agreement with existing literature

Framework supports future research in valve mechanics and repair

Abstract

Atrioventricular valve regurgitation is a significant cause of morbidity and mortality in patients with acquired and congenital cardiac valve disease. Image-derived computational modeling of atrioventricular valves has advanced substantially over the last decade and holds particular promise to inform valve repair in small and heterogeneous populations which are less likely to be optimized through empiric clinical application. While an abundance of computational biomechanics studies have investigated mitral and tricuspid valve disease in adults, few studies have investigated application to vulnerable pediatric and congenital heart populations. Further, to date, investigators have primarily relied upon a series of commercial applications that are neither designed for image-derived modeling of cardiac valves, nor freely available to facilitate transparent and reproducible valve science. To address this deficiency, we aimed to build an open-source computational framework for the image-derived biomechanical analysis of atrioventricular valves. In the present work, we integrated an open-source valve modeling platform, SlicerHeart, and an open-source biomechanics finite element modeling software, FEBio, to facilitate image-derived atrioventricular valve model creation and finite element analysis. We present a detailed verification and sensitivity analysis to demonstrate the fidelity of this modeling in application to 3D echocardiography-derived pediatric mitral and tricuspid valve models. Our analyses achieved excellent agreement with those reported in the literature. As such, this evolving computational framework offers a promising initial foundation for future development and investigation of valve mechanics, in particular collaborative efforts targeting the development of improved repairs for children with congenital heart disease.