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Updated: Apr 8, 2026

Dynamic Measurement and Imaging of Capillaries, Arterioles, and Pericytes in Mouse Heart
Published on: July 29, 2020
Measurement and modeling of coronary blood flow
Matthew D Sinclair1, Jack Lee1, Andrew N Cookson1
1Division of Imaging Sciences and Biomedical Engineering, British Heart Foundation (BHF) Centre of Excellence, King's College London, London, UK.
Insights
Computational modeling integrates coronary structure and function data across scales. This approach bridges experimental and clinical research, offering new insights into ischemic heart disease and guiding clinical practice.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Computational Biology
Background:
- Ischemic heart disease is a leading global cause of death.
- Understanding coronary structure-function interactions is vital for disease treatment.
- Coronary blood flow presents challenges due to multi-scale behaviors.
Purpose of the Study:
- To explore the integration of coronary structure and function across different scales.
- To establish computational modeling as a framework for understanding coronary blood flow.
- To bridge the gap between experimental findings and clinical applications in cardiovascular disease.
Main Methods:
- Utilizing computational modeling to integrate mechanistic behaviors across spatial and temporal scales.
- Combining experimental data with mathematical models of physical laws.
- Leveraging state-of-the-art computational techniques to analyze coronary circulation.
Main Results:
- Computational modeling provides a unique framework to integrate multi-scale physiological behaviors.
- The approach integrates imaging and measurements with mathematical descriptions.
- New insights into coronary physiology and disease are generated.
Conclusions:
- Computational modeling serves as a crucial bridge between experimental and clinical cardiovascular research.
- This integrated approach enhances understanding of ischemic heart disease.
- Applications include optimizing medical technologies and guiding clinical practice.
Abstract:
Ischemic heart disease that comprises both coronary artery disease and microvascular disease is the single greatest cause of death globally. In this context, enhancing our understanding of the interaction of coronary structure and function is not only fundamental for advancing basic physiology but also crucial for identifying new targets for treating these diseases. A central challenge for understanding coronary blood flow is that coronary structure and function exhibit different behaviors across a range of spatial and temporal scales. While experimental studies have sought to understand this feature by isolating specific mechanisms, in tandem, computational modeling is increasingly also providing a unique framework to integrate mechanistic behaviors across different scales. In addition, clinical methods for assessing coronary disease severity are continuously being informed and updated by findings in basic physiology. Coupling these technologies, computational modeling of the coronary circulation is emerging as a bridge between the experimental and clinical domains, providing a framework to integrate imaging and measurements from multiple sources with mathematical descriptions of governing physical laws. State-of-the-art computational modeling is being used to combine mechanistic models with data to provide new insight into coronary physiology, optimization of medical technologies, and new applications to guide clinical practice.
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