Artificial intelligence-enabled plaque characterization from coronary computed tomography establishes basis of angina in women with nonobstructive atherosclerosis
https://www.nature.com/articles/s43856-026-01668-6
Publish Date: 2026-05-28 13:24:00
Source Domain: www.nature.com
- Study Focus: The study investigated ischemic symptoms in women with non-obstructive coronary artery disease (CAD), particularly within the context of angina severity.
- Methodology: Women with INOCA were part of the WARRIOR trial, including analysis using a Seattle Angina Questionnaire (SAQ), coronary CT angiography (CCTA), and AI-based software.
- Findings: Among the participants, more severe angina correlated with higher non-calcified plaque (NCP) burden, low-attenuation plaque (LAP), and machine-learning ischemia risk scores (ML-IRS).
- Demographic Information: Patients with more severe angina were younger and had higher cholesterol levels but received statins less frequently compared to those with less severe angina.
- Risk Factors: Multivariate analysis indicated that higher NCP and LAP burden, along with higher ML-IRS, were associated with more severe reported angina, measured by lower SAQ scores.
- Conclusion: The study concluded that high-risk atherosclerotic plaque characteristics in women with INOCA are linked to more severe angina, emphasizing the pathophysiological differences contributing to ischemic symptoms.
