3D Heart Electromechanical Simulation With Tissue-Level Cell Modeling
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Solution Overview
Problem
Current computational models struggle to accurately simulate the complex interactions between electrophysiological and mechanical processes in the human heart, particularly in conditions such as myocardial infarction and congenital defects, due to high computational demands and the need for detailed modeling of cardiac tissue heterogeneities, which makes it impractical to model every single cell.
Innovation Solution
A method using the Finite Element Method (FEM) with Finite Differences Method (FDM) to discretize heart models, incorporating electromechanical and electrophysiological aspects, and employing parallel computing to simulate a virtual population with varied physiological parameters, including ion channel dynamics and tissue properties, to account for individual and population-level variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed modeling of every single cell is performed, then simulation accuracy is improved, but computational demand becomes prohibitive
Solution Approach 1:
The heart model is segmented into multiple tissue types (e.g., myocardium, Purkinje tissue, endocardium, epicardium) rather than modeling every individual cell. Each tissue type is represented by a representative cell model that captures the essential electrophysiological properties of that tissue category, enabling simulation at the tissue level without prohibitive computational cost.
Solution Approach 2:
Different tissue types are assigned distinct electrophysiological properties and cell models appropriate to their local characteristics. For example, Purkinje tissue receives a different cell model than myocardium, and each region is modeled with properties specific to its physiological function, achieving local accuracy without global over-modeling.
2Manufacturing precision
If computational resources are increased to model every cell, then simulation detail is improved, but ease of operation deteriorates
Solution Approach 1:
Instead of modeling every cell in the heart, the approach models a representative subset of cell types for each tissue region. This partial action provides sufficient detail for studying tissue-level electrophysiology and drug effects while maintaining computational tractability and operational practicality.
Solution Approach 2:
Representative cell models serve as copies or proxies for the actual cells in each tissue type. These simplified copies capture the essential behavior needed for simulation purposes without requiring the full complexity of every individual cell, making the modeling process practical and operable.
3Reliability
If heterogeneous tissue properties are modeled in detail, then physiological accuracy is improved, but device complexity increases
Solution Approach 1:
The model incorporates local tissue heterogeneity by assigning different cell models and electrophysiological properties to different tissue types (myocardium, Purkinje, endocardium, epicardium). Each region maintains its specific physiological characteristics while the overall model structure remains manageable through systematic organization.
Solution Approach 2:
The heart model is constructed as a composite of multiple tissue types, each with its own electrophysiological properties. This composite structure allows the model to represent the heterogeneous nature of cardiac tissue while organizing complexity into manageable, physically meaningful components.
Data Source
AI summary
A computer-generated, three-dimensional heart model established with an electromechanical aspect and an electrophysiological aspect. The model may include tissue types and associated cell models comprising a system of ordinary differential equations describing properties for that tissue type, at least describing cell kinetics for ion channels of that tissue type. A three-dimensional model of a heart is constructed by creating a volume mesh comprising tissue type regions corresponding to each of the plurality of tissue types, wherein each tissue type region defines a local muscular fibre orientation in each tissue type region to correspond to a local alignment of muscular cells. The method further comprises running coupled three-dimensional electromechanical and electrophysiological simulations across the volume mesh. One or more derived physiological parameters are determined for the virtual patient.