Simultaneous couch and gantry dynamic arc rotation (CG‐Darc) in the treatment of breast cancer with accelerated partial breast irradiation (APBI): a feasibility study
Bibliographic record
Abstract
The purpose of this study was to compare the dosimetry of CG-Darc with three-dimensional conformal radiation therapy (3D CRT) and volumetric-modulated arc therapy (RapidArc) in the treatment of breast cancer with APBI. CG-Darc plans were generated using two tangential couch arcs combined with a simultaneous noncoplanar gantry arc. The dynamic couch arc was modeled by consecutive IMRT fields at 10° intervals. RapidArc plans used a single partial arc with an avoidance sector, preventing direct beam exit into the thorax. CG-Darc and RapidArc plans were compared with 3D CRT in 20 patients previously treated with 3D CRT (group A), and in 15 additional patients who failed the dosimetric constraints of the Canadian trial and of NSABP B-39/RTOG 0413 for APBI (group B). CG-Darc resulted in superior target coverage compared to 3D CRT and RapidArc (V95%: 98.2% vs. 97.1% and 95.7%). For outer breast lesions, CG-Darc and RapidArc significantly reduced the ipsilateral breast V50% by 8% in group A and 15% in group B (p < 0.05) as compared with 3D CRT. For inner and centrally located lesions, CG-Darc resulted in significant ipsilateral lung V10% reduction when compared to 3D CRT and RapidArc (10.7% vs. 12.6% and 20.7% for group A, and 15.1% vs. 25.2% and 27.3% for group B). Similar advantage was observed in the dosimetry of contralateral breast where the percent maximum dose for CG-Darc, 3D CRT, and RapidArc were 3.9%, 6.3%, and 5.8% for group A and 4.3%, 9.2%, and 6.3% for group B, respectively (p < 0.05). CG-Darc achieved superior target coverage while decreasing normal tissue dose even in patients failing APBI dose constraints. Consequently, this technique has the potential of expanding the use of APBI to patients currently ineligible for such treatment. Modification of the RapidArc algorithm will be necessary to link couch and gantry rotation with variable dose rate and, therefore, enable the use of CG-Darc in clinical practice.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".