scholarly journals RELATIONSHIP OF ORIFICE GEOMETRY OF ANOMALOUS CORONARY ARTERIES ARISING FROM OPPOSING CORONARY SINUSES (ACAOS) TO FUNCTIONAL MYOCARDIAL ISCHEMIA AND CLINICAL OUTCOMES: EVALUATION BY 64-DETECTOR ROW CORONARY COMPUTED TOMOGRAPHIC ANGIOGRAPHY

2010 ◽  
Vol 55 (10) ◽  
pp. A42.E401
Author(s):  
Kelly Axsom ◽  
Troy LaBounty ◽  
Jin-Ho Choi ◽  
James K. Min ◽  
Fay Y. Lin
Keyword(s):  
Myocardial Ischemia ◽  
Coronary Arteries ◽  
Computed Tomographic Angiography ◽  
Coronary Computed Tomographic Angiography ◽  
Computed Tomographic ◽  
Outcomes Evaluation ◽  
Tomographic Angiography ◽  
Relationship Of ◽  
Anomalous Coronary ◽  
Anomalous Coronary Arteries

scholarly journals Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence

Open Heart ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. e001832
Author(s):  
Rebecca Jonas ◽  
James Earls ◽  
Hugo Marques ◽  
Hyuk-Jae Chang ◽  
Jung Hyun Choi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Coronary Angiography ◽  
Computed Tomographic Angiography ◽  
Lesion Length ◽  
Coronary Computed Tomographic Angiography ◽  
Younger Patients ◽  
Computed Tomographic ◽  
Calcified Plaque ◽  
Tomographic Angiography ◽  
Relationship Of

ObjectiveThe study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).MethodsThis is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (<50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age <65 and ≥65 years.ResultsThe cohort was 64.4±10.2 years and 29% women. Overall, patients >65 had more PV and CP than patients <65. On a lesion level, patients >65 had more CP than younger patients in both obstructive (29.2 mm3 vs 48.2 mm3; p<0.04) and non-obstructive lesions (22.1 mm3 vs 49.4 mm3; p<0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p<0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients.ConclusionAI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment.

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