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Updated: Nov 15, 2025

In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Multimodal cardiovascular model for hemodynamic analysis: Simulation study on mitral valve disorders
Dibyendu Roy1, Oishee Mazumder1, Aniruddha Sinha1
1TCS Research, Tata Consultancy Services Limited, Kolkata, India.
Insights
This study presents an in-silico cardiac model to analyze valvular heart disease progression. The computational model simulates mitral valve disorders, providing insights into hemodynamic changes and disease severity for better cardiovascular research.
Area of Science:
- Cardiovascular Physiology
- Computational Biology
- Medical Simulation
Background:
- Valvular heart diseases significantly contribute to cardiovascular morbidity and mortality globally.
- In-silico modeling is an emerging tool for cardiovascular research and clinical applications.
- Understanding valvular disease progression requires integrated physiological and hemodynamic analysis.
Purpose of the Study:
- To develop and present an in-silico cardiac computational model for analyzing valvular heart disease.
- To simulate and understand the progression of mitral valve disorders (Mitral Stenosis and Mitral Regurgitation).
- To assess the impact of these disorders on general hemodynamic parameters.
Main Methods:
- A multimodal and multiscale cardiovascular model integrating cardiac electrophysiology and hemodynamics.
- Simulation of an adult cardiovascular system including a four-chambered heart and circulation.
- Analysis of pressure, volume, flow, valve dynamics, and Photoplethysmogram signals in normal and pathological states.
Main Results:
- The model accurately simulates hemodynamic parameters for normal and mitral valve disorder conditions.
- Simulated left atrium and ventricle dimensions correlate with cardiac chamber enlargement in patients.
- Generated physiological parameters align with published data.
Conclusions:
- The developed in-silico model offers a holistic understanding of valvular heart disease effects.
- The model aids in assessing the severity of mitral valve disorders and their hemodynamic consequences.
- It facilitates 'what if' scenario analysis for conditions like stress or exercise.
Abstract:
Valvular heart diseases are a prevalent cause of cardiovascular morbidity and mortality worldwide, affecting a wide spectrum of the population. In-silico modeling of the cardiovascular system has recently gained recognition as a useful tool in cardiovascular research and clinical applications. Here, we present an in-silico cardiac computational model to analyze the effect and severity of valvular disease on general hemodynamic parameters. We propose a multimodal and multiscale cardiovascular model to simulate and understand the progression of valvular disease associated with the mitral valve. The developed model integrates cardiac electrophysiology with hemodynamic modeling, thus giving a broader and holistic understanding of the effect of disease progression on various parameters like ejection fraction, cardiac output, blood pressure, etc., to assess the severity of mitral valve disorders, naming Mitral Stenosis and Mitral Regurgitation. The model mimics an adult cardiovascular system, comprising a four-chambered heart with systemic, pulmonic circulation. The simulation of the model output comprises regulated pressure, volume, and flow for each heart chamber, valve dynamics, and Photoplethysmogram signal for normal physiological as well as pathological conditions due to mitral valve disorders. The generated physiological parameters are in agreement with published data. Additionally, we have related the simulated left atrium and ventricle dimensions, with the enlargement and hypertrophy in the cardiac chambers of patients with mitral valve disorders, using their Electrocardiogram available in Physionet PTBI dataset. The model also helps to create 'what if' scenarios and relevant analysis to study the effect in different hemodynamic parameters for stress or exercise like conditions.
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