A compact mechatronic system for 3D ultrasound guided prostate interventions
Bibliographic record
Abstract
PURPOSE: Ultrasound imaging has improved the treatment of prostate cancer by producing increasingly higher quality images and influencing sophisticated targeting procedures for the insertion of radioactive seeds during brachytherapy. However, it is critical that the needles be placed accurately within the prostate to deliver the therapy to the planned location and avoid complications of damaging surrounding tissues. METHODS: The authors have developed a compact mechatronic system, as well as an effective method for guiding and controlling the insertion of transperineal needles into the prostate. This system has been designed to allow guidance of a needle obliquely in 3D space into the prostate, thereby reducing pubic arch interference. The choice of needle trajectory and location in the prostate can be adjusted manually or with computer control. RESULTS: To validate the system, a series of experiments were performed on phantoms. The 3D scan of the string phantom produced minimal geometric error, which was less than 0.4 mm. Needle guidance accuracy tests in agar prostate phantoms showed that the mean error of bead placement was less then 1.6 mm along parallel needle paths that were within 1.2 mm of the intended target and 1 degree from the preplanned trajectory. At oblique angles of up to 15 degrees relative to the probe axis, beads were placed to within 3.0 mm along a trajectory that were within 2.0 mm of the target with an angular error less than 2 degrees. CONCLUSIONS: By combining 3D TRUS imaging system to a needle tracking linkage, this system should improve the physician's ability to target and accurately guide a needle to selected targets without the need for the computer to directly manipulate and insert the needle. This would be beneficial as the physician has complete control of the system and can safely maneuver the needle guide around obstacles such as previously placed needles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".