Prospective pilot study utilizing changes in quantitative values obtained on serial fluorine‐18 fluorodeoxyglucose (<sup>18</sup>F‐FDG) positron emission tomography–computed tomography (PET/CT) in dogs with appendicular osteosarcoma before and after stereotactic body radiation therapy (SBRT) and carboplatin chemotherapy to assess for prediction of survival and therapeutic effectiveness
Bibliographic record
Abstract
Abstract Serial fluorine 18 fluorodeoxyglucose (18F‐FDG) positron emission tomography–CT (PET/CT) is commonly used in human oncology to prognosticate and evaluate for therapeutic effectiveness. In this pilot study, dogs with naturally occurring appendicular osteosarcoma were evaluated with serial 18F‐FDG PET/CT in an attempt to assess for response to therapy, prognostic factors, and appropriateness of imaging intervals. Fourteen dogs were enrolled in the trial. All dogs had the initial 18F‐FDG PET/CT (PET1), with nine dogs having their end‐of‐therapy 18F‐FDG PET/CT (EoT PET) 3 months after stereotactic body radiation therapy (SBRT) to the primary tumor. The median percent change from the PET1 to the EoT PET for the standard uptake value maximum (SUVmax%) was −58% (range: −17 to −88%), metabolic tumor volume (MTV%) was −99.8% (range: −65 to −100%), and total lesion glycolysis (TLG%) was −99.8% (range: −75 to −100%), all of which were significant (P < .05, <.05, and <.05, respectively). On evaluation, it was found that volumes of GTV and CTV were significant for survival (P < .05 and <.05), MTV1, TLG1, and SUVmax on the EoT PET (SUVmaxEoT) were predictive of metastasis (P < .05), and the SUVmax% was significantly correlated to the time to first event (P < .05). Based on this data, serial 18F‐FDG PET/CT performed 3 months after SBRT can show a significant reduction in avidity, and the quantitative data collected may help predict metastatic disease in canine appendicular osteosarcoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".