An Optimization Framework to Estimate Patient-Specific Passive Cardiac Mechanics

Core Concepts

This study introduces an inverse finite element analysis (iFEA) framework to estimate the passive mechanical properties of cardiac tissue using time-dependent medical image data. The framework employs a nested optimization scheme to simultaneously determine the stress-free reference configuration and the best-fit material parameters that align the FEA-predicted deformation with the image-based motion.

Abstract

The authors developed an inverse finite element analysis (iFEA) framework to personalize the passive mechanical behavior of the myocardium using time-resolved 4D computed tomographic (CT) data. The key highlights are:

The framework utilizes a nested optimization scheme, where the outer iterations optimize the material parameters using traditional optimization methods, while the inner iterations estimate the stress-free reference configuration using an augmented Sellier's algorithm.

The framework employs structurally-based anisotropic hyperelastic constitutive models (Holzapfel-Ogden and Guccione-McCulloch) and physiologically relevant boundary conditions to simulate myocardial mechanics.

The framework is tested on biventricular and left atrial myocardium models derived from cardiac CT images of a healthy subject and three patients with hypertrophic obstructive cardiomyopathy (HOCM).

A rigorous sensitivity analysis is performed to assess the impact of optimization methods, fiber direction parameters, mesh size, initial parameters, and perturbations to optimal material parameters.

The performance of the iFEA framework is compared against an assumed power-law-based pressure-volume relation, typically used for single-phase image acquisition.

The authors demonstrate the capability of the iFEA framework to personalize passive cardiac mechanics using time-resolved image data, which can be valuable for analyzing myocardial pathology and evaluating treatment plans.

Stats

The myocardial density in the reference configuration is 1.055 g/cm3.
The bulk modulus (κ) is 106 dyn/cm2.
The dynamic viscosity (μv) is 103 dyn-s/cm2.

Quotes

None

Key Insights Distilled From

An Optimization Framework to Personalize Passive Cardiac Mechanics

by Lei Shi,Ian ... at arxiv.org 04-04-2024

https://arxiv.org/pdf/2404.02807.pdf

Deeper Inquiries

How can the estimated passive material parameters be used to tune the active contraction component of the myocardium for a comprehensive patient-specific cardiac mechanics model

The estimated passive material parameters obtained from the iFEA framework can be utilized to tune the active contraction component of the myocardium in a patient-specific cardiac mechanics model by integrating them into a coupled multiscale cardiac mechanics modeling framework. This integration allows for the comprehensive simulation of the heart's functioning, considering both passive and active components.
The passive material parameters, such as the stiffness and anisotropy of the myocardium, play a crucial role in determining how the heart deforms under different loading conditions. By accurately estimating these parameters through the iFEA framework, the model can better represent the passive behavior of the myocardium during diastole.
To tune the active contraction component, the estimated passive material parameters can be used as a baseline to calibrate the active stress-strain relationship within the myocardium. This calibration involves adjusting parameters related to the active contraction of the cardiac muscle, such as the activation and contraction kinetics, to match the observed behavior of the heart during systole. By iteratively adjusting these parameters and simulating the cardiac mechanics model, a more accurate representation of the heart's function in health and disease can be achieved.

What are the potential limitations of the current iFEA framework, and how can it be further improved to handle more complex cardiac pathologies beyond HOCM

The current iFEA framework, while robust for estimating passive material parameters of the myocardium, may have some limitations when applied to more complex cardiac pathologies beyond HOCM. Some potential limitations include:

Model Complexity: More complex cardiac pathologies may require additional material parameters or constitutive models to accurately capture the biomechanical behavior of the heart. The current framework may need to be extended to incorporate these complexities.

Data Variability: The framework relies on image data acquired at specific cardiac phases, which may not fully capture the dynamic nature of certain cardiac pathologies. Incorporating dynamic imaging techniques or patient-specific data from multiple phases could enhance the accuracy of the model.

Computational Efficiency: Handling more complex pathologies may increase the computational demands of the framework. Optimization algorithms and numerical methods may need to be optimized for efficiency to handle larger datasets and more intricate models.

To improve the iFEA framework for handling complex cardiac pathologies, considerations could include enhancing the constitutive models to account for specific disease characteristics, integrating multi-scale modeling approaches, incorporating patient-specific data from various imaging modalities, and optimizing the computational algorithms for scalability and accuracy.

Given the importance of the left atrium in various cardiovascular diseases, how can the iFEA framework be extended to study the active mechanics of the left atrium and its interaction with the ventricles

To extend the iFEA framework to study the active mechanics of the left atrium (LA) and its interaction with the ventricles, several key steps can be taken:

Model Development: Develop patient-specific LA models using time-resolved imaging data, similar to the biventricular models. Incorporate physiological boundary conditions and fiber orientations specific to the LA myocardium.

Constitutive Modeling: Implement an anisotropic constitutive model, such as the Holzapfel-Ogden or Guccione-McCulloch model, tailored for the LA myocardium. Adjust material parameters to capture the unique mechanical behavior of the LA.

Boundary Conditions: Apply appropriate boundary conditions on the LA model, considering the interaction with the pulmonary veins, mitral valve, and surrounding structures. Ensure the model accurately represents LA mechanics during different phases of the cardiac cycle.

Integration with Ventricular Models: Couple the LA model with the existing biventricular models to simulate the coordinated function of the atria and ventricles. This integration allows for a comprehensive understanding of the heart's mechanics and interactions.

By extending the iFEA framework to study the active mechanics of the LA and its interaction with the ventricles, researchers and clinicians can gain valuable insights into the role of the LA in cardiovascular diseases and treatment planning.