The effect of seed anisotropy on brachytherapy dose distributions using 125I and 103Pd
Bibliographic record
Abstract
We have evaluated the effect of the anisotropy of individual seeds on dose distributions for permanent prostate implants using 125I and 103Pd. The dose distributions were calculated for various implants using both the line source and point source calculational formalisms, for two different models of 125I and 103Pd seeds. The dose distributions were compared using cumulative dose volume histograms (DVH) and cumulative difference dose volume histograms (deltaDVH) for the prostate target volume and for the rectum surface. The DVHs could not distinguish between the dose distributions from isotropic and non-isotropic seeds. However, the deltaDVHs were useful in determining the fraction of the target volume for which the difference between the dose distribution for line sources and for point sources exceeded a threshold value. The dose distributions were calculated (1) for all the seeds oriented co-linearly, along either the x-, y-, or z-axis, and (2) for the seeds at randomized orientations, more closely resembling the clinical situation. For all cases, there was a significant difference in the effect of seed anisotropy from the different seed types. For the geometrically simpler test cases with a small number of seeds, the effect of anisotropy on the dose distribution was too large to ignore for any of the seed types investigated. For the idealized pre-plan case, the effect was much smaller. For clinical prostate implants, the calculations done with seeds oriented co-linearly along the z-axis (needle implant axis) were a reasonable approximation for those from simulations of seeds with randomized orientations. Again, the effect of anisotropy varied drastically between different seed models, and also between different clinical cases. However, the effect of anisotropy must be considered in the context of all the other uncertainties in clinical brachytherapy treatments.
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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".