Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes
Background: Coronary artery disease (CAD) manifests differently between sexes, with data suggesting females develop more non-calcified plaques that traditional calcium-centric tools may not detect. Methods: We conducted a retrospective cohort study of 100 individuals with low total atheroma volume (...
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Elsevier
2025-10-01
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| Series: | International Journal of Cardiology: Heart & Vasculature |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352906725001617 |
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| author | Zoee D’Costa Ronald P. Karlsberg Geoffrey W. Cho |
| author_facet | Zoee D’Costa Ronald P. Karlsberg Geoffrey W. Cho |
| author_sort | Zoee D’Costa |
| collection | DOAJ |
| description | Background: Coronary artery disease (CAD) manifests differently between sexes, with data suggesting females develop more non-calcified plaques that traditional calcium-centric tools may not detect. Methods: We conducted a retrospective cohort study of 100 individuals with low total atheroma volume (TAV) < 250 mm3 using artificial intelligence (AI)-enabled coronary computed tomography angiography (CCTA) to assess sex-based differences in coronary plaque composition. Plaque subtypes included calcified, non-calcified, and low-density non-calcified atheroma volumes. Results: Females had significantly lower total (p = 0.018) and non-calcified plaque (p < 0.001) burden compared to males. Calcified (p = 0.52) and low-density non-calcified (p = 0.16) plaque volumes did not differ significantly. Age was a consistent predictor of plaque volume across most subtypes. Conclusions: Despite low overall plaque burden, males demonstrated a higher non-calcified plaque burden than females. This finding contrasts with previous literature and underscores the potential of AI-enabled CCTA to detect subclinical coronary disease, particularly in low-risk cohorts. These results support the use of comprehensive plaque profiling in both sexes to improve early risk stratification. |
| format | Article |
| id | doaj-art-827b1aee7dce42a99b13dbfaf2a9a8b0 |
| institution | Matheson Library |
| issn | 2352-9067 |
| language | English |
| publishDate | 2025-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Cardiology: Heart & Vasculature |
| spelling | doaj-art-827b1aee7dce42a99b13dbfaf2a9a8b02025-07-29T04:12:37ZengElsevierInternational Journal of Cardiology: Heart & Vasculature2352-90672025-10-0160101758Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumesZoee D’Costa0Ronald P. Karlsberg1Geoffrey W. Cho2David Geffen School of Medicine at the University of California Los Angeles, United States; Corresponding author at: 757 Westwood Plaza, Los Angeles, CA, 90095, United States.David Geffen School of Medicine at the University of California Los Angeles, United States; Cedars-Sinai Heart Institute, United States; Cardiovascular Research Foundation of Southern California, United StatesDavid Geffen School of Medicine at the University of California Los Angeles, United States; Cardiovascular Research Foundation of Southern California, United StatesBackground: Coronary artery disease (CAD) manifests differently between sexes, with data suggesting females develop more non-calcified plaques that traditional calcium-centric tools may not detect. Methods: We conducted a retrospective cohort study of 100 individuals with low total atheroma volume (TAV) < 250 mm3 using artificial intelligence (AI)-enabled coronary computed tomography angiography (CCTA) to assess sex-based differences in coronary plaque composition. Plaque subtypes included calcified, non-calcified, and low-density non-calcified atheroma volumes. Results: Females had significantly lower total (p = 0.018) and non-calcified plaque (p < 0.001) burden compared to males. Calcified (p = 0.52) and low-density non-calcified (p = 0.16) plaque volumes did not differ significantly. Age was a consistent predictor of plaque volume across most subtypes. Conclusions: Despite low overall plaque burden, males demonstrated a higher non-calcified plaque burden than females. This finding contrasts with previous literature and underscores the potential of AI-enabled CCTA to detect subclinical coronary disease, particularly in low-risk cohorts. These results support the use of comprehensive plaque profiling in both sexes to improve early risk stratification.http://www.sciencedirect.com/science/article/pii/S2352906725001617Artificial intelligenceCoronary computed tomography angiographyCoronary atheroma volumeSex differencesNon-calcified plaquePlaque composition |
| spellingShingle | Zoee D’Costa Ronald P. Karlsberg Geoffrey W. Cho Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes International Journal of Cardiology: Heart & Vasculature Artificial intelligence Coronary computed tomography angiography Coronary atheroma volume Sex differences Non-calcified plaque Plaque composition |
| title | Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| title_full | Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| title_fullStr | Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| title_full_unstemmed | Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| title_short | Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| title_sort | artificial intelligence assisted ccta quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes |
| topic | Artificial intelligence Coronary computed tomography angiography Coronary atheroma volume Sex differences Non-calcified plaque Plaque composition |
| url | http://www.sciencedirect.com/science/article/pii/S2352906725001617 |
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