Influence of breast composition and interseed attenuation in dose calculations for post-implant assessment of permanent breast<sup>103</sup>Pd seed implant
Bibliographic record
Abstract
The impact of tissue heterogeneity and interseed attenuation is studied in post-implant evaluation of five clinical permanent breast (103)Pd seed implants using the Monte Carlo (MC) dose calculation method. Dose metrics for the target (PTV) as well as an organ at risk (skin) are used to visualize the differences between a TG43-like MC method and more accurate MC methods capable of considering the breast tissue heterogeneity as well as the interseed attenuation. PTV dose is reduced when using a breast tissue model instead of water in MC calculations while the dose to the skin is increased. Furthermore, we investigate the effect of varying the glandular/adipose proportion of the breast tissue on dose distributions. The dose to the PTV (skin) decreases (increases) with the increasing adipose proportion inside the breast. In a complete geometry and compared to a TG43-like situation, the average PTV D(90) reduction varies from 3.9% in a glandular breast to 35.5% when the breast consists entirely of adipose. The skin D(10) increases by 28.2% in an entirely adipose breast. The results of this work show the importance of an accurate and patient-dependent breast tissue model to be used in the dosimetry for this kind of low energy implant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".