360-degree 3D transvaginal ultrasound system for high-dose-rate interstitial gynaecological brachytherapy needle guidance
Bibliographic record
Abstract
Treatment for gynaecological cancers often includes brachytherapy; in particular, in high-dose-rate (HDR) interstitial brachytherapy, hollow needles are inserted into the tumour and surrounding area through a template in order to deliver the radiation dose. Currently, there is no standard modality for visualizing needles intra-operatively, despite the need for precise needle placement in order to deliver the optimal dose and avoid nearby organs, including the bladder and rectum. While three-dimensional (3D) transrectal ultrasound (TRUS) imaging has been proposed for 3D intra-operative needle guidance, anterior needles tend to be obscured by shadowing created by the template’s vaginal cylinder. We have developed a 360-degree 3D transvaginal ultrasound (TVUS) system that uses a conventional two-dimensional side-fire TRUS probe rotated inside a hollow vaginal cylinder made from a sonolucent plastic (TPX). The system was validated using grid and sphere phantoms in order to test the geometric accuracy of the distance and volumetric measurements in the reconstructed image. To test the potential for visualizing needles, an agar phantom mimicking the geometry of the female pelvis was used. Needles were inserted into the phantom and then imaged using the 3D TVUS system. The needle trajectories and tip positions in the 3D TVUS scan were compared to their expected values and the needle tracks visualized in magnetic resonance images. Based on this initial study, 360-degree 3D TVUS imaging through a sonolucent vaginal cylinder is a feasible technique for intra-operatively visualizing needles during HDR interstitial gynaecological brachytherapy.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".