Prospective evaluation of pretreatment and intratreatment FDG PET‐CT SUV stability in primary head and neck cancer
Bibliographic record
Abstract
PURPOSE: To evaluate standardized uptake value (SUV) stability on pretreatment and intratreatment 18-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-CT) in patients undergoing definitive CRT for head and neck cancer (HNC). METHODS: Primary tumor and nodal volumes of interest (VOIs) from HNC patients were contoured on the pretreatment and intratreatment PET-CT by two independent observers. SUV stability was measured with intersection calculations (DICE, overlap fraction, center to center) between the VOIs at threshold levels of 50%, 60%, 70%, 80%, and 90% of the SUV maximum. RESULTS: The mean calculated DICE of the 50%, 60%, 70%, 80%, 90% SUV threshold was 0.53, 0.48, 0.41, 0.28, and 0.12, respectively. The mean calculated overlap fraction was 0.71, 0.65, 0.58, 0.43, and 0.2, respectively. Center-center difference demonstrates spatial variability of 7.8, 8.2, 8.6, 9.5, and 11.2 mm for these SUV subvolumes of interest. CONCLUSIONS: HNC subvolumes defined by SUV thresholding technique in FDG PET-CT imaging do not remain physically stable during (chemo)RT. HIGHLIGHTS: All pretreatment and intratreatment SUV thresholds (50%-90%) overlap indexes are low during the course of (chemo)radiation. Pretreatment and intratreatment center to center variation further corroborates that all FDG threshold volumes do not remain stable during treatment. No difference in SUV threshold stability was seen between p16 positive and negative tumors.
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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) | 0.001 | 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".