Quantification of Myocardial Blood Flow with /sup 13/N-Ammonia and /sup 82/Rb PET - OSEM vs. FBP Reconstruction
Bibliographic record
Abstract
OSEM is a standard for image reconstruction in positron emission tomography (PET). However, OSEM has not been compared with filtered back projection (FBP) for the quantification of myocardial blood flow (MBF) with13N-ammonia (NH3) and82Rb PET. 12 subjects with1. Normal population databases were also created for NH3 and Rb using a net retention model. The databases comprised population mean and standard deviation (SD) polar-maps at rest, stress and stress/rest. There were no consistent differences between LV-median K1values generated with OSEM or FBP, although the rest NH3 K1value did decrease by 16% with OSEM (p=0.01). Peak blood values were consistently reduced by 5-10% with OSEM. At rest, the normal population database SD with OSEM was 10% higher for Rb (p=0.02) and 5% higher for NH3 (p=0.02). Conversely, the stress SD was decreased by 15% with OSEM for Rb (p<0.001) and 9% for NH3 (p<0.001). Stress/rest SD also decreased with OSEM by 15% for NH3 (p<0.001), and tended to decrease by 4% for Rb (p=0.12). The measured normal range (population SD) of stress flow and stress/rest reserve appears to be smaller with OSEM vs. FBP, which may be advantageous for the diagnosis of CAD with Rb and NH3 PET
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".