Tomosynthesis-based intraoperative dosimetry for low dose rate prostate brachytherapy
Bibliographic record
Abstract
The aim of this study is to develop an intraoperative dose assessment procedure that can be performed after an I-125 prostate seed implantation, while the patient is still under anaesthesia. To accomplish this, we reconstruct the 3D position of each seed and co-register it with the prostate contour acquired with a transrectal ultrasound (TRUS) probe. Our seed detection method involves a tomosynthesis-based filtered reconstruction of the volume of interest requiring 7 projections acquired over an angle of 60o with an isocentric imaging system. The co-registration between the tomosynthesis-based seed positions and the TRUS-based prostate contour is based on the planned position. A phantom and a clinical study (25 patients) were carried out to validate the technique. In the patient study, the automatic tomosynthesis-based reconstruction yields a seed detection rate of 96.7% and less than 2.6% false-positive. The seed localization error obtained with a phantom study is 0.4 ± 0.4 mm. The co-registration method based on planned seed position has proved to be not accurate enough for dosimetric purposes. We believe that this technique may be used to discover considerable underdosage and to improve the dosimetric coverage by potentially reimplanting additional seeds.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".