Use of Needle Track Detection to Quantify the Displacement of Stranded Seeds Following Prostate Brachytherapy
Bibliographic record
Abstract
We aim to compute the movement of permanent stranded implant brachytherapy radioactive sources (seeds) in the prostate from the planned seed distribution to the intraoperative fluoroscopic distribution, and then to the postimplant computed tomography (CT) distribution. We present a novel approach to matching the seeds in these distributions to the plan by grouping the seeds into needle tracks. First, we identify the implantation axis using a sample consensus algorithm. Then, we use a network flow algorithm to group seeds into their needle tracks. Finally, we match the needles from the three stages using both their transverse plane location and the number of seeds per needle. We validated our approach on eight clinical prostate brachytherapy cases, having a total of 871 brachytherapy seeds distributed in 193 needles. For the intraoperative and postimplant data, 99.31% and 99.41% of the seeds were correctly assigned, respectively. For both the preplan to fluoroscopic and fluoroscopic to CT registrations, 100% of the needles were correctly matched. We show that there is an average intraoperative seed displacement of 4.94±2.42 mm and a further 2.97±1.81 mm of postimplant movement. This information reveals several directional trends and can be used for quality control, treatment planning, and intraoperative dosimetry that fuses ultrasound and fluoroscopy.
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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".