Diagnostic utility of longitudinal flow gradient for diagnosis of obstructive coronary artery disease in Rubidium-82 positron emission tomography
Bibliographic record
Abstract
The longitudinal myocardial blood flow (MBF) gradient, reflecting the basal-to-apical decline in stress MBF, has been proposed as a non-invasive marker for obstructive coronary artery disease (CAD). However, its clinical utility in Rubidium-82 ( 82 Rb) positron emission tomography (PET) remains unestablished. This single-center retrospective study included consecutive patients who underwent rest/dipyridamole-stress 82 Rb PET myocardial perfusion imaging and invasive coronary angiography within 90 days from January 2012 to December 2019. Stress MBF and longitudinal gradients (basal-to-apical differences) were quantified in left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) territories. Coronary territories were stratified by coronary artery calcification (CAC) and perfusion defects (PD) into groups A (CAC−, PD−), B (CAC+, PD−), and C (PD+). Associations with CAD burden and diagnostic performance for obstructive CAD (≥50% angiographic stenosis) were evaluated using receiver operating characteristic analysis. Of 1,516 patients screened, 396 (median age: 68 years; 30.6% female) were included, contributing 1,077 coronary territories (LAD: 391; LCX: 377; RCA: 309). In LAD territory, longitudinal MBF gradients increased with CAD burden (p<0.001) and improved diagnostic accuracy beyond relative perfusion and stress MBF (AUC 0.774 vs. 0.743, p=0.002). Conversely, gradients in LCX and RCA territories decreased with increasing CAD burden (both p<0.001) and did not improve diagnostic performance (LCX: AUC 0.704 vs. 0.715, p=0.267; RCA: AUC 0.727 vs. 0.723, p=0.698). Longitudinal stress MBF gradients derived from 82 Rb PET may enhance diagnostic accuracy for obstructive CAD in the LAD territory. No additional diagnostic value was observed in LCX or RCA territories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".