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Intravascular imaging of coronary artery: Bridging the gap between clinical needs and technical advances
Atefeh Abdolmanafi1, Luc Duong1, Ragui Ibrahim2
1Department of Software and IT Engineering, École de Technologie Supérieure, Montréal, Canada; Division of Pediatric Cardiology and Research Center, Centre Hospitalier Universitaire Sainte-Justine, Montréal, Canada.
Insights
Coronary artery disease, a leading cause of death, requires better intravascular imaging analysis. This review bridges clinical needs with medical image analysis advances for improved coronary plaque assessment.
Area of Science:
- Cardiovascular Medicine
- Medical Image Analysis
- Biomedical Engineering
Background:
- Coronary artery disease (CAD) is the primary global cause of mortality, with atherosclerosis and plaque rupture being major contributors.
- Millions of deaths annually underscore the urgent need for improved diagnostic and analytical tools for CAD.
- Existing intravascular imaging technologies for coronary arteries show a significant disparity between clinical requirements and current capabilities.
Purpose of the Study:
- To identify and delineate the gaps between current clinical knowledge and recent advancements in medical image analysis for coronary arteries.
- To guide the development of efficient computational models for image analysis that align with precise clinical needs and tissue characteristics.
- To facilitate the integration of clinically validated intracoronary plaque features into advanced image analysis models.
Main Methods:
- Review of current literature on intravascular imaging of coronary arteries.
- Analysis of clinical features of intracoronary plaques relevant to image analysis.
- Identification of discrepancies between clinical demands and technological solutions in medical image analysis.
Main Results:
- A significant gap exists between the clinical need for precise coronary artery imaging analysis and the current state of medical image analysis technology.
- Detailed clinical features of intracoronary plaques are crucial for developing effective mathematical and biomedical models.
- Integration of clinician-validated knowledge is essential for enhancing the efficiency and accuracy of coronary image analyses.
Conclusions:
- Bridging the gap between clinical needs and technological advancements in medical image analysis is critical for improving outcomes in coronary artery disease.
- Future research should focus on developing computational models that incorporate detailed clinical features of intracoronary plaques.
- Collaborative efforts between clinicians and researchers are vital to leverage state-of-the-art coronary image analysis for better patient care.
Abstract:
Coronary artery disease is the leading cause of mortality worldwide. Almost seven million deaths are reported each year due to coronary disease. Coronary artery events in the adult are primarily due to atherosclerosis with seventy-five percent of the related mortality caused by plaque rupture. Despite significant progress made to improve intravascular imaging of coronary arteries, there is still a large gap between clinical needs and technical developments. The goal of this review is to identify the gap elements between clinical knowledge and recent advances in the domain of medical image analysis. Efficient image analysis computational models should be designed with respect to the exact clinical needs, and detailed features of the tissues under review. In this review, we discuss the detailed clinical features of the intracoronary plaques for mathematical and biomedical researchers. We emphasize the importance of integrating this clinical knowledge validated by clinicians to investigate the potentially effective models for proper features efficiency in the scope of leveraging the state-of-the-art of coronary image analyses.
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