Appropriate Use Criteria for PET Myocardial Perfusion Imaging
Bibliographic record
Abstract
In the last decade, myocardial perfusion imaging (MPI) with PET has emerged to play a pivotal role in the clinical routine process for the detection of hemodynamically significant obstructive coronary artery disease (CAD) and cardiovascular risk stratification (1-5). The high spatial and contrast resolution in concert with photon attenuation-free images of PET have led to high image quality associated with the highest sensitivity and specificity of PET/CT perfusion imaging in the detection and characterization of CAD (1,2,6,7). In addition, the noninvasive evaluation and quantification of global and regional myocardial blood flow (MBF) in milliliters per gram per minute during hyperemic stress and at rest, as well as the calculation of the resulting myocardial flow reserve (MFR), extends the scope of standard MPI from the detection of advanced and flow-limiting epicardial CAD to a comprehensive assessment of ischemic burden. This improved scope results not only from the traditionally sought significant left main or multivessel disease, but also from the more recently appreciated cardiac effects of nonobstructive CAD and coronary microvascular disease (CMD), which conveys important diagnostic and incremental prognostic information
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.001 |
| 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".