Evaluation of stimulus-effect relations in left ventricular growth using a simple multiscale model.

Area of Science:

• Cardiology
• Biomedical Engineering
• Computational Biology

Background:

• Cardiac growth is a natural adaptation to increased blood flow demand.
• Cardiac diseases can induce abnormal cardiac growth, necessitating predictive models.
• Existing cardiac growth models vary in stimulus-effect relationships and growth constraints.

Purpose of the Study:

• To evaluate cardiac growth in response to aortic and mitral regurgitation and aortic stenosis using a multiscale model.
• To investigate the impact of stress- and strain-based stimuli on cardiac growth.
• To assess the influence of growth stimuli on left ventricular cavity and wall volume, and hemodynamic performance.

Main Methods:

• Utilized a zero-dimensional, multiscale model of the left ventricle.
• Simulated cardiac growth under conditions of aortic regurgitation, mitral regurgitation, and aortic stenosis.
• Examined various combinations of stress- and strain-based stimuli.

Main Results:

• All simulations reached a converged state without requiring growth constraints.
• Considering at least one stress-based stimulus yielded the most promising results for cardiac growth prediction.
• The model demonstrated the ability to predict changes in cavity volume, wall volume, and hemodynamic performance.

Conclusions:

• A simplified left ventricular mechanics model can effectively evaluate cardiac growth laws.
• Stress-based stimuli are crucial for accurate prediction of cardiac growth in disease states.
• This approach offers a foundation for developing clinically valuable predictive models for abnormal cardiac growth.