Quantitative PET Comparing Gated with Nongated Acquisitions Using a NEMA Phantom with Respiratory-Simulated Motion
Why this work is in the frame
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Bibliographic record
Abstract
UNLABELLED: This study evaluated the use of gated versus nongated PET acquisitions for absolute quantification of radioisotope concentration (RC) in a respiratory motion-simulated moving phantom filled with radioactive spheres and background for both 2-dimensional (2D) and 3-dimensional (3D) acquisitions. METHODS: An image-quality phantom with all 6 spheres filled with the same (18)F RC (range, 19-62 kBq/mL) was scanned with PET/CT at rest and in motion with and without gating. The background was filled with (18)F solution to yield sphere-to-background ratios of approximately 5, 10, 15, and 20 to 1. Both 2D and 3D acquisitions were used for all combinations. Respiratory motion was simulated by using a motor-driven plastic platform to move the phantom periodically with a displacement of 2 cm and a cycle time of 5.8 s. For gated acquisitions, the phantom was tracked using a real-time position management system. Images were reconstructed, and regions of interest with the same sizes as the actual spheres were manually placed on axial slices to determine maximum and mean pixel RC. A threshold method (70% and 94% for 2D and 3D modes) was also used to determine a mean voxel RC. All values were compared with the expected RC; percentage differences were calculated for each sphere. To reduce partial-volume effects, only data for the 4 largest spheres were analyzed. RESULTS: The mean pixel method was the only method with linear responses for all 3 scan types, enabling direct comparisons. The ranges of RC percentage differences were underestimated for all scan types (using the mean pixel method). The overall mean percentage differences were 37, 49, and 41 in 2D mode and 40, 51, and 41 in 3D mode for static, nongated, and gated acquisitions, respectively. Gated acquisitions improved quantification (by reducing underestimation) over nongated acquisitions by 8% and 10% for 2D and 3D modes. CONCLUSION: In the presence of motion, the use of gated PET acquisitions appears to improve quantification accuracy over nongated acquisitions, almost restoring the results to those observed when the phantom is static.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it