Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response

TL;DR

This study applies advanced uncertainty quantification methods to assess how variability in myocardial stiffness and fiber orientation affects left ventricle deformation predictions, emphasizing the importance of accurate fiber modeling.

Contribution

It introduces a novel application of polynomial chaos expansion and Karhunen-Loève expansion for uncertainty quantification in cardiac mechanics models.

Findings

Fiber orientation variability significantly influences model outputs.

Material stiffness parameters impact global deformation measures.

Uncertainty in fiber architecture surpasses other sources of variability.

Abstract

Computational cardiac modelling is a mature area of biomedical computing, and is currently evolving from a pure research tool to aiding in clinical decision making. Assessing the reliability of computational model predictions is a key factor for clinical use, and uncertainty quantification (UQ) and sensitivity analysis are important parts of such an assessment. In this study, we apply new methods for UQ in computational heart mechanics to study uncertainty both in material parameters characterizing global myocardial stiffness and in the local muscle fiber orientation that governs tissue anisotropy. The uncertainty analysis is performed using the polynomial chaos expansion (PCE) method, which is a non-intrusive meta-modeling technique that surrogates the original computational model with a series of orthonormal polynomials over the random input parameter space. In addition, in order to study variability in the muscle fiber architecture, we model the uncertainty in orientation of the fiber field as an approximated random field using a truncated Karhunen-Lo\'eve expansion. The results from the UQ and sensitivity analysis identify clear differences in the impact of various material parameters on global output quantities. Furthermore, our analysis of random field variations in the fiber architecture demonstrate a substantial impact of fiber angle variations on the selected outputs, highlighting the need for accurate assignment of fiber orientation in computational heart mechanics models.