Abstract 4369150: AI-enabled Plaque Phenotype Analysis of Coronary Computed Tomography Angiography Findings in Patients with Nonacute Chest Pain using FFR <sub>CT</sub> : Results from the PRECISE Trial
Bibliographic record
Abstract
Introduction: Advances in coronary computed tomography angiography (CCTA) have enhanced the possibilities for assessment and quantification of coronary artery disease (CAD). Using data from the CCTA arm of the PRECISE randomized trial (non-acute chest pain needing testing), we examined the extent and diffuseness of coronary plaque burden using novel CCTA-derived metrics. Methods: All stable, symptomatic patients from the PRECISE randomized trial who underwent CCTA for evaluation of suspected CAD and had ≥50% diameter stenosis in at least one vessel were included, N=196. 3-vessel CAD patterns were assessed using FFR CT and AI-enabled quantitative plaque analysis (Heartflow). Nadir FFR CT was defined as total drop in FFR CT across the entire vessel. The FFR CT drop over a stenosis was termed stenosis FFR CT (sFFR CT ). The decrement in FFR CT due to diffuse disease was termed diffuse FFR CT (dFFR CT ) and defined as 1 – nadir FFR CT – sFFR CT . Patients were stratified into four groups (NoHEM, FOC, DIF and FOC+DIF) using cohort medians of 0.10 (sFFR CT ) and 0.13 (dFFR CT ) (Table). The Seattle Angina Questionnaire (SAQ) was used to assess symptoms. Results: No hemodynamic disease (NoHEM), FOC, DIF and FOC+DIF were present in 21.5%, 28.6%, 29.6% and 20.4% of patients respectively. Clinical characteristics were similar between groups (Table). FOC and DIF+FOC had the lowest FFR CT nadir values as well as the highest stenosis FFR CT (both p<0.001). Per-patient total plaque volume (TPV, mm 3 ) was higher in FOC and DIF+FOC compared to NoHEM and DIF (p=0.008; Figure). Per-patient noncalcified plaque volume (NCPV, mm 3 ) followed a similar pattern (p=0.004), although % NCPV did not differ (0.86). Per-patient calcified plaque volume (CPV, mm 3 ) and %CPV did not differ between groups (p=0.12 and 0.86). Conclusion: CCTA allows for a more refined CAD plaque burden categorization by separating the FFR CT losses due to focal stenoses and diffuse CAD. Patients with focal or mixed (focal and diffuse) CAD phenotypes were not distinguishable by clinical characteristics, risk burden or angina severity. However, they exhibited higher plaque volumes, particularly noncalcified plaque, than those with no NoHEM or only diffuse disease. Further studies are necessary to examine the prognostic and therapeutic implications of these findings.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".