A dosimetric parameter to limit chest wall toxicity in SABR of NSCLC
Bibliographic record
Abstract
Objective: Chest wall (CW) toxicity (rib fracture and/or pain) is a recognized complication of stereotactic ablative radiotherapy (SABR) for non-small-cell lung cancer. The aim of this study was to evaluate the frequency of CW toxicity following SABR and to propose a new dosimetric parameter. Methods: We reviewed the charts and SABR plans from patients treated for T1–T2N0 peripheral non-small-cell lung cancer between 2009 and 2015. The CW structure was created through a 3-cm expansion of the lung. The median dose delivered to the planning target volume was 60 Gy. SABR was delivered in three fractions for patients with CW V 30 < 30 cm3. If the CW V 30 exceeded 30 cm3, five fractions were used, and the plan was optimized based on CW V 37 (biologically equivalent to the V 30 of three-fraction plans). Results: In 6 years, 361 lesions from 356 patients were treated (3 fractions: 297; 5 fractions: 64). The median follow-up was 16 months. 23 patients (6.5%) developed CW toxicity after a median time of 10 months following treatment. The mean CW V 30/V 37 was 21 cm3 for patients with CW toxicity and 17 cm3 for patients without toxicity (p < 0.05). The 2-year local control and the CW toxicity rates were similar, whether patients received three or five fractions (97% vs 96% and 7% vs 5%). Conclusion: When the CW V 30 is >30 cm3, altered fractionation combined with V 37 optimization can limit CW toxicity. Advances in knowledge: The CW V 37 is a suggested dosimetric parameter adapted to fractionation that may potentially limit CW toxicity after lung SABR.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".