Artificial-intelligence-assisted CCTA quantifies sex differences in coronary atherosclerotic burden at low atheroma volumes.

Zoee D'Costa, Ronald P Karlsberg, Geoffrey W Cho

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Article in International journal of cardiology. Heart & vasculature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 · What the graph read from it

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1 citing paper in PubMed.

Highlights recently published in the International Journal of Cardiology Heart & Vasculature on sex differences in cardiovascular disease diagnosis and management.International journal of cardiology. Heart & vasculature · 2026
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5 · Who and what money

Authors and funding

3 authors.

Zoee D'CostaDavid Geffen School of Medicine at the University of California Los Angeles, United States.

Ronald P KarlsbergDavid Geffen School of Medicine at the University of California Los Angeles, United States.

Geoffrey W ChoDavid Geffen School of Medicine at the University of California Los Angeles, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 mm 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.

Indexed as

Artificial intelligenceCardiovascular risk stratificationCoronary atheroma volumeCoronary computed tomography angiographyNon-calcified plaquePlaque compositionSex differences

Identifiers

PMID40761307

DOI10.1016/j.ijcha.2025.101758

PMCPMC12319248

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