Dose reduction in LDR brachytherapy by implanted prostate gold fiducial markers
Bibliographic record
Abstract
PURPOSE: The dosimetric impact of gold fiducial markers (FM) implanted prior to external beam radiotherapy of prostate cancer on low dose rate (LDR) brachytherapy seed implants performed in the context of combined therapy was investigated. METHODS: A virtual water phantom was designed containing a single FM. Single and multi source scenarios were investigated by performing Monte Carlo dose calculations, along with the influence of varying orientation and distance of the FM with respect to the sources. Three prostate cancer patients treated with LDR brachytherapy for a recurrence following external beam radiotherapy with implanted FM were studied as surrogate cases to combined therapy. FM and brachytherapy seeds were identified on post implant CT scans and Monte Carlo dose calculations were performed with and without FM. The dosimetric impact of the FM was evaluated by quantifying the amplitude of dose shadows and the volume of cold spots. D(90) was reported based on the post implant CT prostate contour. RESULTS: Large shadows are observed in the single source-FM scenarios. As expected from geometric considerations, the shadows are dependent on source-FM distance and orientation. Large dose reductions are observed at the distal side of FM, while at the proximal side a dose enhancement is observed. In multisource scenarios, the importance of shadows appears mitigated, although FM at the periphery of the seed distribution caused underdosage (<prescription dose). In clinical cases, the FM reduced the dose to some voxels by up to 50% and generated shadows with extents of the order of 4 mm. Within the prostate contour, cold spots (<95% prescription dose) of the order of 20 mm(3) were observed. D(90) proved insensitive to the presence of FM for the cases selected. CONCLUSIONS: There is a major local impact of FM present in LDR brachytherapy seed implant dose distributions. Therefore, reduced tumor control could be expected from FM implanted in tumors, although our results are too limited to draw conclusions regarding clinical significance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".