Applications of tissue heterogeneity corrections and biologically effective dose volume histograms in assessing the doses for accelerated partial breast irradiation using an electronic brachytherapy source
Bibliographic record
Abstract
A low-energy electronic brachytherapy source (EBS), the model S700 Axxent x-ray device developed by Xoft Inc., has been used in high dose rate (HDR) intracavitary accelerated partial breast irradiation (APBI) as an alternative to an Ir-192 source. The prescription dose and delivery schema of the electronic brachytherapy APBI plan are the same as the Ir-192 plan. However, due to its lower mean energy than the Ir-192 source, an EBS plan has dosimetric and biological features different from an Ir-192 source plan. Current brachytherapy treatment planning methods may have large errors in treatment outcome prediction for an EBS plan. Two main factors contribute to the errors: the dosimetric influence of tissue heterogeneities and the enhancement of relative biological effectiveness (RBE) of electronic brachytherapy. This study quantified the effects of these two factors and revisited the plan quality of electronic brachytherapy APBI. The influence of tissue heterogeneities is studied by a Monte Carlo method and heterogeneous 'virtual patient' phantoms created from CT images and structure contours; the effect of RBE enhancement in the treatment outcome was estimated by biologically effective dose (BED) distribution. Ten electronic brachytherapy APBI cases were studied. The results showed that, for electronic brachytherapy cases, tissue heterogeneities and patient boundary effect decreased dose to the target and skin but increased dose to the bones. On average, the target dose coverage PTV V(100) reduced from 95.0% in water phantoms (planned) to only 66.7% in virtual patient phantoms (actual). The actual maximum dose to the ribs is 3.3 times higher than the planned dose; the actual mean dose to the ipsilateral breast and maximum dose to the skin were reduced by 22% and 17%, respectively. Combining the effect of tissue heterogeneities and RBE enhancement, BED coverage of the target was 89.9% in virtual patient phantoms with RBE enhancement (actual BED) as compared to 95.2% in water phantoms without RBE enhancement (planned BED). About 10% increase in the source output is required to raise BED PTV V(100) to 95%. As a conclusion, the composite effect of dose reduction in the target due to heterogeneities and RBE enhancement results in a net effect of 5.3% target BED coverage loss for electronic brachytherapy. Therefore, it is suggested that about 10% increase in the source output may be necessary to achieve sufficient target coverage higher than 95%.
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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 | 0.008 |
| 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".