Advancement in computational simulation and validation of congenital heart disease: a review

Area of Science:

• Biomedical Engineering
• Cardiovascular Research
• Computational Science

Background:

• Improved congenital heart disease (CHD) management has increased infant survival rates.
• Assessing the long-term effectiveness of CHD treatments remains challenging.
• Computational modeling offers a powerful tool for evaluating treatment outcomes in CHD.

Purpose of the Study:

• To provide a comprehensive overview of computational modeling applications in CHD.
• To categorize CHD computational models based on affected structures (large blood vessels, heart chambers, multiple structures).
• To discuss advancements, future directions, and validation techniques for CHD computational modeling.

Main Methods:

• Review of existing literature on computational modeling in CHD.
• Categorization of models based on anatomical involvement in CHD.
• Highlighting multiscale and multiphysics modeling approaches.
• Discussion of proposed validation techniques including 3D printing and particle image velocimetry (PIV).

Main Results:

• Computational modeling effectively evaluates CHD, categorized by affected structures.
• Multiscale and multiphysics modeling provide a complete representation of cardiac function and circulation.
• Future directions include incorporating growth, remodeling, detailed conduction systems, and myocardial infarction.

Conclusions:

• Computational modeling is crucial for assessing long-term CHD treatment efficacy.
• Advanced simulation techniques and validation methods are vital for improving model accuracy.
• Further development in computational CHD modeling promises enhanced patient care and outcomes.