Collimator selection, acquisition speed, and visual assessment of 131I-tositumomab biodistribution in a phantom model.
Bibliographic record
Abstract
UNLABELLED: (131)I-Tositumomab has been used in treating patients with non-Hodgkin's lymphoma. It is generally recommended that high-energy collimators be used to image patients before they receive (131)I-tositumomab therapy, to determine the effective half-life for therapeutic dose and gross biodistribution. Because many nuclear medicine departments do not possess high-energy collimators, this study was designed to assess the suitability of using medium-energy collimators. The effect of scanning speed was also investigated, in an attempt to optimize the acquisition time. METHODS: Measurements were taken using an elliptic anthropomorphic torso phantom and an organ-scanning phantom fitted with fillable spheres (1-5 cm in diameter) and organ inserts. Three phantom studies were performed with differing initial (131)I concentrations in the organs, the spheres, and the thoracic and abdominal chambers. Images were acquired with both high-energy and medium-energy collimators and at acquisition speeds of 20 and 100 cm/min. The half-life for each combination (study/collimator/speed) was calculated from a linear fit of the data. The contrast of the tumor sphere was assessed using 2 identical regions, placed on and beside the sphere, and averaged over several time points. Biodistribution and image quality were visually assessed by 2 independent observers. RESULTS: Measured half-life values and visual assessment of biodistribution showed no significant difference between the 2 collimators (P = 0.32) or acquisition speeds (P = 0.85). A significant difference in the contrast of the tumor spheres was observed between the 2 collimators (P < 0.01) but not between acquisition speeds. Visual assessment of the images showed increased noise on the image acquired at 100 cm/min, although this noise did not affect lesion detectability. CONCLUSION: Measured half-life is not significantly different between the 2 collimators; hence, calculation of the residence time would be nearly the same. Medium-energy collimators can be used to accurately calculate the (131)I-tositumomab therapeutic dose and detect alterations in biodistribution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".