Cardiac Sparing with Personalized Treatment Planning for Early-stage Left Breast Cancer
Bibliographic record
Abstract
Purpose To compare cardiac doses of different whole-breast optimization schemes including free-breathing (FB) tangential radiotherapy (TRT), deep-inspiration breath-hold (DIBH) TRT, and FB helical tomotherapy (HT). Methods Early-stage left-sided breast cancer patients who underwent breast-conserving surgery followed by adjuvant radiotherapy were included in the study. Planning images included FB and DIBH CT scans acquired in the same supine treatment position with both arms abducted. A hypofractionated regimen of 42.5 Gy in 16 fractions was used. Clinical target volume delineation was aided through the use of a radio-opaque wire. A 7-mm margin was used in generating the planning target volumes. TRT plans were generated both in FB and DIBH. For the FB tomotherapy technique, a first plan (Tomo 1) was optimized limiting the maximum contralateral breast dose to 3.1 Gy. A second tomotherapy plan (Tomo 2) focused on the reduction of the mean heart dose without controlling the contralateral breast dose. All plans were optimized to obtain an equivalent planning target volume (PTV) coverage of ≥95% of the prescribed dose while minimizing the dose to organs at risk. Results Twenty-three patients treated between October 2012 and March 2016 were included in this retrospective study. Eleven patients (48%) had at least one major cardiovascular risk factors including one patient (4%) with a history of myocardial infarction. Six patients (26%) had been exposed to cardiotoxic chemotherapy agents. The average mean dose to the heart was 3.1 Gy with FB TRT, 1.1 with DIBH TRT, 2.4 Gy for Tomo 1, and 1.5 Gy for Tomo 2. The mean dose to the left anterior descending artery was 27.0 Gy, 8.0 Gy, 13.7 Gy and 6.6 Gy for FB TRT, DIBH TRT, Tomo 1 and Tomo 2 plans respectively. Conclusion Different cardiac-sparing optimization schemes are possible when treating left breast cancer. Although DIBH offers clear mean heart dose reductions, tomotherapy can be an interesting alternative treatment modality to spare the heart and coronary vessels, notably in patients who cannot comply with DIBH.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".