Quantification of regional myocardial blood flow in a canine model of stunned and infarcted myocardium: comparison of rubidium-82 positron emission tomography with microspheres
Bibliographic record
Abstract
BACKGROUND: Myocardial viability and quantification of regional myocardial blood flow (MBF) are important for the diagnosis of heart disease. Positron emission tomography is the current gold standard for determining myocardial viability, but most positron-emitting perfusion tracers require an on-site cyclotron. Rubidium-82 ((82)Rb) is a myocardial perfusion tracer that is produced using an on-site generator. This study investigates (82)Rb-measured MBF in canine models of stunned and infarcted myocardium compared with selected measurements obtained concurrently using microspheres. METHODS: Myocardial stunning and infarction were created in canines by occluding the left anterior descending for 15 min and 2 h, respectively. Stunning was produced in all animals; six animals were reperfused after the 2 h occlusion, whereas the other six animals remained occluded permanently. Regional MBF was measured in each group during rest and dobutamine stress at acute and chronic (8 weeks postinsult) time points using dynamic (82)Rb perfusion imaging and radioactively labeled microspheres. RESULTS: Average resting MBF with microspheres and Rb was 0.68+/-0.02 versus 0.73+/-0.01 (P<0.001) in nonischemic tissue, and 0.53+/-0.03 versus 0.42+/-0.02 (P<0.001) in the region-at-risk tissue, respectively. Average MBF during stress with microspheres and Rb was 2.78+/-0.15 versus 3.53+/-0.16 (P<0.05) in the nonischemic tissue, and 1.90+/-0.20 versus 2.31+/-0.26 (P = NS) in the region-at-risk tissue, respectively. CONCLUSION: Despite the small significant differences, the dynamic (82)Rb measurements provide estimates of MBF in stunned and acutely and chronically infarcted tissue at rest and during hyperemia that correspond with clinical interpretation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".