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Updated: Sep 12, 2025
Author Spotlight: Enhancing Coronary Artery Revascularization
Published on: September 15, 2023
Understanding coronary bypass grafts from mechanical constitutive models to machine learning: A review
Aisa Rassoli1, Shirin Changizi2, Farnaz Soltani1
1Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
Insights
Coronary artery bypass grafting (CABG) outcomes improve with arterial grafts over vein grafts. Advanced computational and AI tools are crucial for predicting graft failure and enhancing surgical planning for better patient results.
Area of Science:
- Cardiovascular Surgery
- Biomedical Engineering
- Medical Imaging
Background:
- Cardiovascular diseases are a leading cause of death, often due to blocked arteries.
- Coronary artery bypass grafting (CABG) uses grafts to restore heart blood flow.
- Saphenous vein grafts (SVGs) have high re-occlusion rates due to intimal hyperplasia and atherosclerosis.
Purpose of the Study:
- To review current graft materials and research in CABG.
- To explore the role of mechanical characterization, simulation, and AI in improving surgical planning.
- To identify limitations and future directions for optimizing CABG outcomes.
Main Methods:
- Review of existing literature on CABG graft materials and patency rates.
- Analysis of mechanical properties of different graft types (vein vs. artery).
- Exploration of computational modeling and artificial intelligence applications in predicting graft performance.
Main Results:
- Arterial grafts (mammary artery, radial artery) show superior long-term patency compared to SVGs.
- Digital tools like mechanical characterization, numerical simulation, and AI offer predictive insights into graft issues.
- These tools aid surgeons in informed decision-making for better surgical planning.
Conclusions:
- Arterial grafts are preferable to SVGs for long-term CABG success.
- Computational and AI-driven approaches are vital for enhancing CABG surgical planning and predicting outcomes.
- Further development of advanced tools is necessary to minimize graft failure and improve clinical results.
Abstract:
Cardiovascular diseases remain the leading cause of mortality worldwide, primarily resulting from the narrowing or blockage of blood vessels. Coronary artery bypass grafting (CABG) is a common surgical intervention that restores blood flow to the heart by using alternative vessels as grafts. Although saphenous vein grafts (SVGs) are frequently utilized in these procedures, they are prone to re-occlusion within 10 years, largely due to intimal hyperplasia and the development of atherosclerosis. In contrast, grafts using the mammary artery (MA) and radial artery demonstrate significantly better long-term patency and are less susceptible to occlusion. Mechanical characterization, numerical simulation, and artificial intelligence models are becoming essential to enhance surgical planning and outcomes. These digital tools provide predictive insights on intimal thickening and restenosis from medical images, thereby assisting surgeons in making well-informed decisions. This review explores the various types of grafts and the latest research in this field, focusing on graft materials, their mechanical properties, computational techniques, artificial intelligence models related to bypass surgery, and the resulting clinical implications. By highlighting the limitations of current methodologies, this review underscores the critical need for the research community to develop more advanced tools to optimize grafting outcomes.
