Does 5 + 5 Equal Better Radiation Treatment Plans in Head and Neck Cancers?
Bibliographic record
Abstract
PURPOSE: Accurate contouring in head and neck cancer (HNC) is critical. International consensus guidelines recommend the 5 + 5 mm rule for expansions around the primary tumor, wherein high- and low-dose clinical target volumes (CTV-P1 and CTV-P2, respectively) are created using successive 5 mm expansions on the gross tumor volume. To our knowledge, the necessity of a low-dose CTV-P2 has never been assessed; therefore, we evaluated the dosimetric impact of adding a CTV-P2 expansion using the 5 + 5 mm rule compared with contouring with a high-dose CTV-P1 alone. METHODS AND MATERIALS: A retrospective study of clinically delivered (chemo)radiation therapy treatment plans for HNC was conducted. All patients were treated with 70 Gy in 35 fractions using volumetric modulated arc therapy in a single phase. CTV-P2 was retrospectively contoured per guidelines as a 5 mm expansion on CTV-P1 from the clinical plan, carving off specified barriers to spread. We used a 5 mm planning target volume (PTV) expansion. Our primary outcome was whether 95% of the volume of the PTV for the CTV-P2 contour (ie, PTV-P2) received at least 56 Gy. To assess dose falloff, the coverage of a PTV ring structure was created by subtracting PTV-P1 from PTV-P2. RESULTS: Twenty-seven patients from 4 HNC subsites (base of tongue, tonsil, hypopharynx, and supraglottic larynx) were included. In all 108 treatment plans, at least 95% of the PTV-P2 structure received at least 56 Gy. The minimum volume of the PTV-P2 structure receiving at least 56 Gy was 97.4%. Eight of 108 treatment plans had borderline coverage of the PTV ring substructure alone. CONCLUSIONS: Adding a CTV-P2 structure using the 5 + 5 mm rule had no dosimetric impact, adds contouring time, adds treatment planning complexity, and could potentially introduce errors. The 5 + 5 mm rule may have value in other settings, such as when smaller PTV margins are used, and warrants further evaluation with prospective or randomized studies.
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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) | 0.000 | 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".