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Artificial intelligence for advanced analysis of coronary plaque
Marly van Assen1,2, Philipp von Knebel Doeberitz1,2,3, Arshed A Quyyumi4
1Department of Radiology and Imaging Sciences, Emory University, Inc. 1365 Clifton Road NE, Suite-AT503, Atlanta, GA 30322, USA.
Artificial intelligence (AI) enhances coronary artery disease analysis by automating complex quantitative measures like plaque burden and radiomics. This integration makes advanced diagnostic tools feasible for clinical practice, improving patient care.
Area of Science:
- Cardiology and Medical Imaging
- Artificial Intelligence in Healthcare
Background:
- Coronary artery disease (CAD) analysis is evolving with quantitative biomarkers such as plaque burden, high-risk plaque features, CT-derived fractional flow reserve, and radiomics.
- These advanced analyses show promise for diagnosis and prognosis in research but are often labor-intensive and time-consuming for routine clinical practice.
Purpose of the Study:
- To explore the role of artificial intelligence (AI) in automating and improving the efficiency of quantitative coronary artery disease analysis.
- To assess AI's potential to make advanced CAD biomarkers clinically feasible without increasing costs or workload.
Main Methods:
- Review of current advancements in AI applications for quantitative coronary plaque analysis.
- Discussion on how AI facilitates the automation of complex imaging biomarkers for CAD.
Main Results:
- AI significantly increases efficiency and reduces human error and reader variability in quantitative plaque analysis.
- AI-driven automation makes advanced CAD analysis methods practical for daily clinical use.
Conclusions:
- Artificial intelligence is crucial for integrating advanced quantitative analysis into routine clinical practice for coronary artery disease.
- AI implementation can improve diagnostic accuracy, prognosis, and overall patient care in cardiology without escalating costs or workload.
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