Robot-assisted 3D-TRUS guided prostate brachytherapy: System integration and validation
Why this work is in the frame
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Bibliographic record
Abstract
Current transperineal prostate brachytherapy uses transrectal ultrasound (TRUS) guidance and a template at a fixed position to guide needles along parallel trajectories. However, pubic arch interference (PAI) with the implant path obstructs part of the prostate from being targeted by the brachytherapy needles along parallel trajectories. To solve the PAI problem, some investigators have explored other insertion trajectories than parallel, i.e., oblique. However, parallel trajectory constraints in current brachytherapy procedure do not allow oblique insertion. In this paper, we describe a robot-assisted, three-dimensional (3D) TRUS guided approach to solve this problem. Our prototype consists of a commercial robot, and a 3D TRUS imaging system including an ultrasound machine, image acquisition apparatus and 3D TRUS image reconstruction, and display software. In our approach, we use the robot as a movable needle guide, i.e., the robot positions the needle before insertion, but the physician inserts the needle into the patient's prostate. In a later phase of our work, we will include robot insertion. By unifying the robot, ultrasound transducer, and the 3D TRUS image coordinate systems, the position of the template hole can be accurately related to 3D TRUS image coordinate system, allowing accurate and consistent insertion of the needle via the template hole into the targeted position in the prostate. The unification of the various coordinate systems includes two steps, i.e., 3D image calibration and robot calibration. Our testing of the system showed that the needle placement accuracy of the robot system at the "patient's" skin position was 0.15 mm+/-0.06 mm, and the mean needle angulation error was 0.07 degrees. The fiducial localization error (FLE) in localizing the intersections of the nylon strings for image calibration was 0.13 mm, and the FLE in localizing the divots for robot calibration was 0.37 mm. The fiducial registration error for image calibration was 0.12 mm and 0.52 mm for robot calibration. The target registration error for image calibration was 0.23 mm, and 0.68 mm for robot calibration. Evaluation of the complete system showed that needles can be used to target positions in agar phantoms with a mean error of 0.79 mm+/-0.32 mm.
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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 it