Sci‐Sat AM(2): Brachy‐02: Image guided brachytherapy (IGBT) for HDR prostate treatment : Pre‐treatment verification using cone beam imaging to determine catheter displacement
Bibliographic record
Abstract
PURPOSE: Prostate HDR brachytherapy utilizes flexible catheters for treatment delivery. Catheters are inserted under US guidance and planning performed on CT images. This study investigates the efficacy of performing kV cone beam imaging prior to treatment to quantify catheter displacement and dose delivered. MATERIALS AND METHODS: Twenty consecutive patients undergoing HDR prostate brachytherapy were planned using CT images. Under US guidance, catheters and four fiducial markers were placed into the prostate. Before treatment, visual check confirmed no movement of the template sutured to the perineum and no movement relative to the template. Cone beam imaging was performed using an isocentric mobile c-arm. Catheters were re-adjusted if required by the Radiation Oncologist. The cone beam images prior to adjustment were later fused with the planning CT. RESULTS AND DISCUSSION: In 17 of the 20 patients, catheter displacements exceeding 0.5cm were observed. Compared to the CT based plan, an average catheter displacement of 1.0cm results in a decrease in the V100 of the prostate by approximately 27%, urethra V120 increased by about 7%, and urethra D10 increased by about 4%. Approximately 65% of patients had average catheter displacements of 1.0cm and larger. Three patients had catheter shifts larger than 2cm. CONCLUSIONS: Catheter movement within the patient can be significant and cone beam imaging prior to treatment delivery provides precise imaging to determine catheter displacement. Cone beam imaging time using an isocentric C-arm is sufficiently short enough (∼ 2 minutes) so as to make this a viable quality assurance tool in the OR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.005 | 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".