AI-Guided Coronary Plaque Analysis from Coronary CTA: An Emerging Paradigm for Personalized Preventive Cardiology.
Coronary artery disease (CAD) remains the leading cause of death worldwide and is driven by atherosclerotic plaque formation. Due to advances in CT technology, coronary CTA (CCTA) has emerged as a leading noninvasive imaging technique to analyze the coronary artery lumen and atherosclerotic plaque....
| Publicado en: | Applied Radiology Vol. 55; no. 3; pp. 1 - 10 |
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| Autores principales: | , , |
| Formato: | diagnostic images pictorial review tables/charts Journal Article |
| Publicado: |
Anderson Publishing Ltd.
May2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194293382&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194293382 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01609963 45A jtl: Applied Radiology issn: 01609963 maglogo: N pubinfo: dt: May2026 vid: 55 iid: 3 pid: 6733 pub: Anderson Publishing Ltd. place: Scotch Plains, New Jersey artinfo: ui: 194293382 194293382 194293382 10.37549/AR-D-25-0140 194293382 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: AI-Guided Coronary Plaque Analysis from Coronary CTA: An Emerging Paradigm for Personalized Preventive Cardiology. aug: au: Basunia, Azfar Jagasia, Dinesh Jamal, Faisal affil: Department of Radiology, Hospital of University of Pennsylvania, Philadelphia, Pennsylvania sug: subj: Artificial Intelligence Utilization Algorithms Utilization Image Processing, Computer Assisted Methods Computed Tomography Angiography Methods Atherosclerosis Radiography Coronary Arteriosclerosis Radiography Cardiovascular Diseases Prevention and Control Coronary Stenosis Diagnosis Risk Assessment Cardiovascular Risk Factors Individualized Medicine Atherosclerosis Physiopathology ab: Coronary artery disease (CAD) remains the leading cause of death worldwide and is driven by atherosclerotic plaque formation. Due to advances in CT technology, coronary CTA (CCTA) has emerged as a leading noninvasive imaging technique to analyze the coronary artery lumen and atherosclerotic plaque. CCTA can characterize plaque types (calcified, noncalcified, and lowattenuation [lipid-rich]) components, which carry different risks. Total plaque burden measured on CCTA, especially the volume of noncalcified plaque, has emerged as a strong predictor of acute coronary syndrome (ACS), independent of traditional risk factors and calcium score. Contemporary CCTA reporting requires manual plaque segmentation, which can be time-intensive and show suboptimal inter- and intraobserver reproducibility. Artificial intelligence-guided quantitative plaque analysis (AI-QPA) algorithms have emerged to address these challenges and increase analytic throughput. In multiple studies over the past few years, AI-QPA has demonstrated superiority over conventional myocardial perfusion imaging and achieved excellent agreement with expert human readers and invasive imaging. Furthermore, the therapeutic basis of lipid-lowering medications was demonstrated using AI-QPA, ushering in an era of personalized preventative cardiology. This review briefly delves into the common AI-QPA workflow, the inner workings, and validation for the 3 most common commercially available AI-QPA platforms: Cleerly, HeartFlow, and PlaqueIQ (Elucid). pubtype: Academic Journal doctype: diagnostic images pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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