Use of a Qualification Phantom for PET Brain Imaging in a Multicenter Consortium: A Collaboration Between the Pediatric Brain Tumor Consortium and the SNMMI Clinical Trials Network
Bibliographic record
Abstract
The purpose of this study was to assess image quality and quantitative brain PET across a multicenter consortium. <b>Methods:</b> All academic centers and children’s hospitals in the Pediatric Brain Tumor Consortium (PBTC) scanned a phantom developed by the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network (SNMMI CTN) for the validation of brain PET studies associated with clinical trials. The phantom comprises 2 separate, fillable sections: a resolution/uniformity section and a clinical simulation section. The resolution/uniformity section is a cylinder 12.7 cm long and 20 cm in diameter; spatial resolution is evaluated subjectively with 2 sets of rods (hot and cold) of varying diameter (4.0, 5.0, 6.25, 7.81, 9.67, and 12.2 mm) and spacing (twice the rod diameter). The clinical simulation section simulates a transverse section of midbrain with ventricles and gray and white matter compartments. If properly filled, hot rods have a 4:1 target-to-background ratio, and gray–to–white matter sections have a 4:1 ratio. Uniformity and image quality were evaluated using the SUV in a small volume of interest as well as subjectively by 2 independent observers using a 4-point scale. <b>Results:</b> Eleven PBTC sites scanned the phantom on 13 PET scanners. The phantom’s complexity led to suboptimal filling, particularly of the hot rod section, in 5 sites. The SUV in the uniformity section was within 10% of unity on only 5 of 13 scanners, although 12 of 13 were subjectively judged to have very good to excellent uniformity. Four of 6 hot rods were discernable by all 13 scanners, whereas 3 of 6 cold rods were discernable by only 5 scanners. Four of 13 scanners had a gray–to–white matter ratio between 3.0 and 5.0 (4.0 is truth); however, 11 of 13 scanners were subjectively judged to have very good or excellent image quality. <b>Conclusion:</b> Eleven sites were able to image a powerful phantom developed by the SNMMI CTN that evaluated image uniformity, spatial resolution, and image quality of brain PET. There was considerable variation in PET data across the PBTC sites, possibly resulting from variations in scanning across the sites due to challenges in filling the phantom.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".