Same day comparison of PET/CT and PET/MR in patients with cardiac sarcoidosis
Bibliographic record
Abstract
Inflammatory cardiac disorders, in particular, sarcoidosis, play an important role in left ventricular dysfunction, conduction abnormalities, and arrhythmias. In this study, we compared the imaging characteristics and diagnostic information obtained when patients were imaged sequentially with PET/CT and then with hybrid PET/MRI on the same day following a single 18F-FDG injection. Ten patients with known or suspected sarcoidosis underwent imaging in sequence of (a) 99mTc-MIBI, (b) 18F-FDG with PET/CT, and (c) 18F-FDG with 3T PET/MRI. Images were compared quantitatively by determination of SUVmax and SUV on a voxel by voxel basis, and qualitatively by two experienced observers. When both platforms were compared quantitatively, similar data for the evaluation of enhanced 18F-FDG uptake were obtained. Qualitatively, there were (1) several instances of normal perfusion with delayed enhancement and/or focal 18F-FDG uptake, (2) comparable enhanced 18F-FDG uptake on PET/CT vs. PET/MRI, and (3) diversity in disease patterns with delayed enhancement only, increased 18F-FDG uptake only, or both. In this limited patient study, PET/CT and PET/MR provided similar diagnostic data for 18F-FDG uptake, and the concurrent acquisition of MR images provided further insight into the disease process.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".