18F‐FMISO PET‐guided dose escalation with multifield optimization intensity‐modulated proton therapy in nasopharyngeal carcinoma
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the radiotherapy planning feasibility of dose escalation with intensity-modulated proton therapy (IMPT) to hypoxic tumor regions identified on 18F-Fluoromisonidazole (FMISO) positron emission tomography and computed tomography (PET-CT) in NPC. MATERIALS AND METHODS: Nine patients with stages T3-4N0-3M0 NPC underwent 18F-FMISO PET-CT before and during week 3 of radiotherapy. The hypoxic volume (GTVhypo) is automatically generated by applying a subthresholding algorithm within the gross tumor volume (GTV) with a tumor to muscle standardized uptake value (SUV) ratio of 1.3 on the 18F-FMISO PET-CT scan. Two proton plans were generated for each patient, a standard plan to 70 Gy and dose escalation plan with upfront boost followed by standard 70GyE plan. The stereotactic boost was planned with single-field uniform dose optimization using two fields to deliver 10 GyE in two fractions to GTVhypo. The standard plan was generated with IMPT with robust optimization to deliver 70GyE, 60GyE in 33 fractions using simultaneous integrated boost technique. A plan sum was generated for assessment. RESULTS: ). The average SUVmax of the hypoxic volume was 2.2 (range 1.44-2.98). All the dose-volume parameters met the planning objectives for target coverage. Dose escalation was not feasible in three of eight patients as the D0.03cc of temporal lobe was greater than 75GyE. CONCLUSIONS: The utility of boost to the hypoxic volume before standard course of radiotherapy with IMPT is dosimetrically feasible in selected patients. Clinical trials are warranted to determine the clinical outcomes of this approach.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".