Reducing the Risk of Secondary Lung Cancer in Treatment Planning of Accelerated Partial Breast Irradiation
Bibliographic record
Abstract
Purpose Adjuvant accelerated partial breast irradiation (APBI) results in low local recurrence risks. However, the survival benefit of adjuvant radiotherapy for low-risk breast cancer might partially be offset by the risk of radiation-induced lung cancer. Reducing the lung dose mitigates this risk, but could result in higher doses to the ipsilateral breast. Different external beam APBI techniques are equally conformal and homogenous, but the intermediate to low-dose distribution differs. Thus, the toxicity risk differs. The purpose of this study is to quantify the trade-off between secondary lung cancer risk and breast dose in treatment planning and to compare an optimal coplanar and non-coplanar technique. Methods A total of 440 APBI treatment plans were generated using automated treatment planning for a coplanar VMAT beam-setup and a non-coplanar robotic stereotactic beam-setup. This enabled an unbiased comparison of two times 11 Pareto-optimal plans for 20 patients, gradually shifting priority from maximum lung sparing to maximum ipsilateral breast sparing. The excess absolute risks of developing lung cancer and breast fibrosis were calculated using the Schneider model and the Avanzo model respectively. Results Prioritizing lung sparing reduced the mean lung dose from 2.2 Gy to as low as 0.3 Gy for the non-coplanar technique and from 1.9 Gy to 0.4 Gy for the coplanar technique, corresponding to a seven-fold and four-fold median reduction of secondary lung cancer risk respectively compared to prioritizing breast sparing. The increase in breast dose resulted in a negligible 0.4% increase in fibrosis risk. The use of non-coplanar beams resulted in lower secondary cancer and fibrosis risks (p<0.001). Lung sparing also reduced the mean heart dose for both techniques. Conclusions The risk of secondary lung cancer of external beam APBI can be dramatically reduced by prioritizing lung sparing during treatment planning. The associated increase in breast dose did not lead to a relevant increase in fibrosis risk. The use of non-coplanar beams systematically resulted in the lowest risks of secondary lung cancer and fibrosis. Prioritizing lung sparing during treatment planning could increase the overall survival of early-stage breast cancer patients by reducing mortality due to secondary lung cancer and cardiovascular toxicity.
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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".