ArticleBiomedical optics express2024
Coronary artery calcification and cardiovascular outcome as assessed by intravascular OCT and artificial intelligence.
Article in Biomedical optics express, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- High-speed, wide-field, fiber-based PS-OCT system with real-time surface Stokes feedback for circular input polarization.Biomedical optics express · 2026Article
- Artificial intelligence in coronary artery calcification scoring: Current progress and future directions.Global cardiology science & practice · 2025Review
- Optical theranostics in ischemic heart disease: from molecular insights to clinical translation.Theranostics · 2025Review
Corrections and comments
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Authors and funding
30 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronary artery calcification (CAC) is a marker of atherosclerosis and is thought to be associated with worse clinical outcomes. However, evidence from large-scale high-resolution imaging data is lacking. We proposed a novel deep learning method that can automatically identify and quantify CAC in massive intravascular OCT data trained using efficiently generated sparse labels. 1,106,291 OCT images from 1,048 patients were collected and utilized to train and evaluate the method. The Dice similarity coefficient for CAC segmentation and the accuracy for CAC classification are 0.693 and 0.932, respectively, close to human-level performance. Applying the method to 1259 ST-segment elevated myocardial infarction patients imaged with OCT, we found that patients with a greater extent and more severe calcification in the culprit vessels were significantly more likely to have major adverse cardiovascular and cerebrovascular events (MACCE) (p < 0.05), while the CAC in non-culprit vessels did not differ significantly between MACCE and non-MACCE groups.
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Registered trials
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