Use of 18F-FDG-PET-CT for Assessment of Response to Neoadjuvant Chemotherapy in Children With Wilms Tumor
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate the predictive value of fluorine-18-fluorodeoxyglucose positron emission tomography with computed tomography (F-FDG-PET-CT) in the assessment of histologic response to neoadjuvant chemotherapy in children with Wilms tumors (WTs). MATERIALS AND METHODS: We prospectively registered 12 patients with WTs who were treated with 2 cycles of neoadjuvant chemotherapy and surgery. All patients underwent sequential F-FDG-PET-CT before (PET-CT1) and after (PET-CT2) neoadjuvant chemotherapy. Maximum standardized uptake value (SUVmax) was measured on PET-CT1 (SUV1) and PET-CT2 (SUV2). The percentage change in SUVmax (SUVmax reduction) was calculated. After surgery the effects of neoadjuvant chemotherapy were graded histopathologically: ≥90% necrosis indicated a good response and <90% necrosis was considered a poor response. The correlation between SUVmax reduction and histologic response was estimated using the Spearman correlation coefficient. RESULTS: Among the 12 patients who underwent PET-CT before and after chemotherapy, SUVmax reduction was significantly different between the good response group and the poor response group (P=0.035). A significant, in terms of P value, correlation was found between pathologic response and SUVmax reduction (r=0.700; 95% confidence interval, 0.060-0.935; P=0.011). A threshold of 66% reduction in SUVmax was identified, with which partition, there were 8 good histologic responders (≥66% decrease in SUVmax) and 4 poor responders. The histologic complete response rate of the good responders was 87.5%, whereas that of poor responders was 0%. SUV1≥7 and SUV2≥2.4 were both considered to be with high risk of recurrence. In patients with SUV1≥7, 4/5 cases relapsed and 4/6 patients with SUV2≥2.4 relapsed. CONCLUSIONS: As there seems to be a good correlation of changes in SUVmax and histologic response, PET-CT has the potential of predicting the response to neoadjuvant chemotherapy in children with WT. SUV1 and SUV2 by themselves might be a good prognosticator of the clinical outcome of WT pediatric patients treated with International Society of Pediatric Oncology protocols, although the reduction rate of SUVmax is much less powerful for prognosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".