Intraoperative 360-deg three-dimensional transvaginal ultrasound during needle insertions for high-dose-rate transperineal interstitial gynecologic brachytherapy of vaginal tumors
Bibliographic record
Abstract
Brachytherapy, a type of radiotherapy, may be used to place radioactive sources into or in close proximity to tumors, providing a method for conformally escalating dose in the tumor and the local area surrounding the malignancy. High-dose-rate interstitial brachytherapy of vaginal tumors requires precise placement of multiple needles through holes in a plastic perineal template to deliver treatment while optimizing dose and avoiding overexposure of nearby organs at risk (OARs). Despite the importance of needle placement, image guidance for adaptive, intraoperative needle visualization, allowing misdirected needles to be identified and corrected during insertion, is not standard practice. We have developed a 360-deg three-dimensional (3-D) transvaginal ultrasound (TVUS) system using a conventional probe with a template-compatible custom sonolucent vaginal cylinder and propose its use for intraoperative needle guidance during interstitial gynecologic brachytherapy. We describe the 3-D TVUS mechanism and geometric validation, present mock phantom procedure results, and report on needle localization accuracy in patients. For the six patients imaged, landmark anatomical features and all needles were clearly visible. The implementation of 360-deg 3-D TVUS through a sonolucent vaginal cylinder provides a technique for visualizing needles and OARs intraoperatively during interstitial gynecologic brachytherapy, enabling implants to be assessed and providing the potential for image guidance.
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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 | 0.000 | 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".