Comparison of sedation and general anesthesia protocols for <sup>18</sup> F‐FDG‐PET/CT studies in dogs and cats: Musculoskeletal uptake and radiation dose to workers
Bibliographic record
Abstract
Abstract In veterinary medicine, PET/CT scans are generally performed with the patient under general anesthesia. The aim of this prospective crossover study was to compare the musculoskeletal uptake of 18 F‐FDG and radiation doses to workers during PET/CT studies of healthy dogs and cats between sedation and general anesthesia. Volume and maximal standard uptake values (SUVmax) values of abnormal 18 F‐FDG uptake in the skeletal musculature, presence of misregistration artifact, and radiation doses to workers for each PET/CT study were recorded. Sedation was associated with increased volume of 18 F‐FDG uptake in the musculature of the thoracic limbs ( p = .01), cervical ( p = .02), and thoracic ( p = .03) spine. Increased volume and SUVmax of the musculature assessed altogether were associated with the lighter degree of sedation ( p = .04 for both). A significant decrease in the odds of misregistration artifact was observed for anesthetized animals in comparison with sedated (OR: 0.0, 95% CI: 0.0–0.0, p = .01). Radiation doses to workers were significantly higher for sedation compared with general anesthesia ( p = .01) and for the anesthesia technician compared with the nuclear medicine technologist ( p = .01). Use of sedation for PET/CT studies in dogs and cats is feasible. However, it is associated with increased physiologic musculoskeletal uptake of 18 F‐FDG in the thoracic limbs, cervical, and thoracic spine, with increased frequency of misregistration artifact, and with increased radiation doses to workers. These limitations can be overcome by recognition of the uptake pattern and monitoring/rotation of the involved staff at institutions where a high caseload is expected.
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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 | 0.001 | 0.000 |
| 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".