SU‐FF‐T‐23: Analysis of Dosimetric Quantities Associated with Partial Breast Brachytherapy
Bibliographic record
Abstract
Purpose: Radiation dose to the heart and lung are a concern in accelerated partial breast irradiation (APBI). This work presents an analysis of the metrics inherent to high dose rate APBI using a brachytherapy source. Method and Materials: Five patients receiving APBI brachytherapy, and 4 patients, who were simulated in both supine and prone position for XRT, were contoured. Dose to the heart and lung were calculated for all potential dwell locations within the contoured breast for a range of potential dwell times. Summary volume and dose metrics were calculated for heart and lung as function of minimum distance (dmin) to the normal structures. The distribution of minimum distances was then compared for the prone and supine patients. Results: Dose metrics such as the D10cc were patient specific and not well suited to parameterization. Volume metrics such as V10Gy tend to have similar behavior and may be characterized as a function of dmin. The characterization provides a measure of the normal tissue dose parameters that are achievable as a function of dmin. While prone position shift the distribution of lung to breast distances towards greater value, the distribution of heart to breast distances is shifted to smaller distances. Conclusion: Characteristic curves of the achievable volume metrics as a function of minimum distance from implant to normal structures are presented. These curves may be helpful in the decision to use APBI brachytherapy based on the location of the cavity. The choice of treatment position affects the distribution of breast tissue, though the effect on distance to heart and lung differs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".