Comparative differences in the atherosclerotic disease burden between the epicardial coronary arteries: quantitative plaque analysis on coronary computed tomography angiography
Bibliographic record
Abstract
AIMS: Anatomic series commonly report the extent and severity of coronary artery disease (CAD), regardless of location. The aim of this study was to evaluate differences in atherosclerotic plaque burden and composition across the major epicardial coronary arteries. METHODS AND RESULTS: A total of 1271 patients (age 60 ± 9 years; 57% men) with suspected CAD prospectively underwent coronary computed tomography angiography (CCTA). Atherosclerotic plaque volume was quantified with categorization by composition (necrotic core, fibrofatty, fibrous, and calcified) based on Hounsfield Unit density. Per-vessel measures were compared using generalized estimating equation models. On CCTA, total plaque volume was lowest in the LCx (10.0 ± 29.4 mm3), followed by the RCA (32.8 ± 82.7 mm3; P < 0.001), and LAD (58.6 ± 83.3 mm3; P < 0.001), even when correcting for vessel length or volume. The prevalence of ≥2 high-risk plaque features, such as positive remodelling or spotty calcification, occurred less in the LCx (3.8%) when compared with the LAD (21.4%) or RCA (10.9%, P < 0.001). In the LCx, the most stenotic lesion was categorized as largely calcified more often than in the RCA and LAD (55.3% vs. 39.4% vs. 32.7%; P < 0.001). Median diameter stenosis was also lowest in the LCx (16.2%) and highest in the LAD (21.3%; P < 0.001) and located more distal along the LCx when compared with the RCA and LAD (P < 0.001). CONCLUSION: Atherosclerotic plaque, irrespective of vessel volume, varied across the epicardial coronary arteries; with a significantly lower burden and different compositions in the LCx when compared with the LAD and RCA. These volumetric and compositional findings support a diverse milieu for atherosclerotic plaque development and may contribute to a varied acute coronary risk between the major epicardial coronary arteries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".