Three-dimensional cardiac computational modelling: methods, features and applications.

Area of Science:

• Biomedical Engineering
• Computational Biology
• Medical Imaging

Background:

• Computational models and biophysical simulations aid in interpreting experimental data for complex diseases like cardiac arrhythmias.
• Three-dimensional (3D) cardiac computational modeling is a growing research area.
• Advances in medical imaging have enabled patient-specific 3D cardiac models.

Purpose of the Study:

• To analyze 60 representative 3D cardiac computational models from the past 50 years.
• To review the components and methods for building 3D cardiac models for biophysical simulation, focusing on cardiac electrophysiology (EP).
• To assess challenges in model development and outline personalization approaches.

Main Methods:

• Analysis of 60 published 3D cardiac computational models.
• Review of components for building cardiac models for biophysical simulation, emphasizing EP.
• Assessment of challenges in data processing, segmentation, substructure inclusion, and meshing.
• Outline of personalization approaches in 3D cardiac modeling.

Main Results:

• Detailed analysis of model information sources, features, development methods, and online availability.
• Identification of necessary components and approaches for cardiac EP simulation.
• Assessment of challenges across the model building pipeline.
• Examples of applications in cardiac EP simulation and model-based image analysis.

Conclusions:

• 3D cardiac computational modeling is a valuable tool for interpreting data and aiding in the prevention, diagnosis, and treatment of cardiac diseases.
• Patient-specific models enhance anatomical representation and cardiac feature accuracy.
• The reviewed models and methods highlight the potential clinical utility of 3D cardiac computational modeling.