Measurement of compensatory arterial remodelling over time with serial coronary computed tomography angiography and 3D metrics
Bibliographic record
Abstract
AIMS: The magnitude of alterations in which coronary arteries remodel and narrow over time is not well understood. We aimed to examine changes in coronary arterial remodelling and luminal narrowing by three-dimensional (3D) metrics from serial coronary computed tomography angiography (CCTA). METHODS AND RESULTS: From a multicentre registry of patients with suspected coronary artery disease who underwent clinically indicated serial CCTA (median interscan interval = 3.3 years), we quantitatively measured coronary plaque, vessel, and lumen volumes on both scans. Primary outcome was the per-segment change in coronary vessel and lumen volume from a change in plaque volume, focusing on arterial remodelling. Multivariate generalized estimating equations including statins were calculated comparing associations between groups of baseline percent atheroma volume (PAV) and location within the coronary artery tree. From 1245 patients (mean age 61 ± 9 years, 39% women), a total of 5721 segments were analysed. For each 1.00 mm3 increase in plaque volume, the vessel volume increased by 0.71 mm3 [95% confidence interval (CI) 0.63 to 0.79 mm3, P < 0.001] with a corresponding reduction in lumen volume by 0.29 mm3 (95% CI -0.37 to -0.21 mm3, P < 0.001). Serial 3D arterial remodelling and luminal narrowing was similar in segments with low and high baseline PAV (P ≥ 0.496). No differences were observed between left main and non-left main segments, proximal and distal segments and side branch and non-side branch segments (P ≥ 0.281). CONCLUSIONS: Over time, atherosclerotic coronary plaque reveals prominent outward arterial remodelling that co-occurs with modest luminal narrowing. These findings provide additional insight into the compensatory mechanisms involved in the progression of coronary atherosclerosis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".