SU‐F‐J‐130: Margin Determination for Hypofractionated Partial Breast Irradiation
Bibliographic record
Abstract
Purpose: To determine the Planning Target Volume (PTV) margin for Hypofractionated Partial Breast Irradiation (HPBI) using the van Herk formalism (M=2.5∑+0.7σ). HPBI is a novel technique intended to provide local control in breast cancer patients not eligible for surgical resection, using 40 Gy in 5 fractions prescribed to the gross disease. Methods: Setup uncertainties were quantified through retrospective analysis of cone‐beam computed tomography (CBCT) data sets, collected prior to (prefraction) and after (postfraction) treatment delivery. During simulation and treatment, patients were immobilized using a wing board and an evacuated bag. Prefraction CBCT was rigidly registered to planning 4‐dimensional computed tomography (4DCT) using the chest wall and tumor, and translational couch shifts were applied as needed. This clinical workflow was faithfully reproduced in Pinnacle (Philips Medical Systems) to yield residual setup and intrafractional error through translational shifts and rigid registrations (ribs and sternum) of prefraction CBCT to 4DCT and postfraction CBCT to prefraction CBCT, respectively. All ten patients included in this investigation were medically inoperable; the median age was 84 (range, 52–100) years. Results: Systematic (and random) setup uncertainties (in mm) detected for the left‐right, craniocaudal and anteroposterior directions were 0.4 (1.5), 0.8 (1.8) and 0.4 (1.0); net uncertainty was determined to be 0.7 (1.5). Rotations >2° in any axis occurred on 8/72 (11.1%) registrations. Conclusion: Preliminary results suggest a non‐uniform setup margin (in mm) of 2.2, 3.3 and 1.7 for the left‐right, craniocaudal and anteroposterior directions is required for HPBI, given its immobilization techniques and online setup verification protocol. This investigation is ongoing, though published results from similar studies are consistent with the above findings. Determination of margins in breast radiotherapy is a paradigm shift, but a necessary step in moving towards hypofractionated regiments, which may ultimately redefine the standard of care for this select patient population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".