Deep Learning From Coronary Computed Tomography Angiography for Atherosclerotic Plaque and Stenosis Quantification and Cardiac Risk Prediction

2021 ◽  
Author(s):  
Andrew Lin ◽  
Nipun Manral ◽  
Priscilla McElhinney ◽  
Aditya Killekar ◽  
Hidenari Matsumoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Risk Prediction ◽  
Atherosclerotic Plaque ◽  
Computed Tomography Angiography ◽  
Coronary Computed Tomography Angiography ◽  
Cardiac Risk ◽  
Coronary Computed Tomography ◽  
Stenosis Quantification

scholarly journals Clinical Relevance of Coronary Computed Tomography Angiography Beyond Coronary Artery Stenosis

2021 ◽  
Author(s):  
Mohammed Nooruddin Meah ◽  
Michelle C. Williams
Keyword(s):  
Computed Tomography ◽  
Coronary Artery ◽  
High Risk ◽  
Atherosclerotic Plaque ◽  
Computed Tomography Angiography ◽  
Coronary Computed Tomography Angiography ◽  
Calcium Score ◽  
Coronary Plaque ◽  
Coronary Computed Tomography ◽  
Low Attenuation Plaque

Background The capabilities of coronary computed tomography angiography (CCTA) have advanced significantly in the past decade. Its capacity to detect stenotic coronary arteries safely and consistently has led to a marked decline in invasive diagnostic angiography. However, CCTA can do much more than identify coronary artery stenoses. Method This review discusses applications of CCTA beyond coronary stenosis assessment, focusing in particular on the visual and quantitative analysis of atherosclerotic plaque. Results Established signs of visually assessed high-risk plaque on CT include positive remodeling, low-attenuation plaque, spotty calcification, and the napkin-ring sign, which correlate with the histological thin-cap fibroatheroma. Recently, quantification of plaque subtypes has further improved the assessment of coronary plaque on CT. Quantitatively assessed low-attenuation plaque, which correlates with the necrotic core of the thin-cap fibroatheroma, has demonstrated superiority over stenosis severity and coronary calcium score in predicting subsequent myocardial infarction. Current research aims to use radiomic and machine learning methods to further improve our understanding of high-risk atherosclerotic plaque subtypes identified on CCTA. Conclusion Despite rapid technological advances in the field of coronary computed tomography angiography, there remains a significant lag in routine clinical practice where use is often limited to lumenography. We summarize some of the most promising techniques that significantly improve the diagnostic and prognostic potential of CCTA. Key Points:  Citation Format

Sign in / Sign up

Export Citation Format

Share Document