Mechanically assisted 3D ultrasound guided prostate biopsy system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are currently limitations associated with the prostate biopsy procedure, which is the most commonly used method for a definitive diagnosis of prostate cancer. With the use of two-dimensional (2D) transrectal ultrasound (TRUS) for needle-guidance in this procedure, the physician has restricted anatomical reference points for guiding the needle to target sites. Further, any motion of the physician's hand during the procedure may cause the prostate to move or deform to a prohibitive extent. These variations make it difficult to establish a consistent reference frame for guiding a needle. We have developed a 3D navigation system for prostate biopsy, which addresses these shortcomings. This system is composed of a 3D US imaging subsystem and a passive mechanical arm to minimize prostate motion. To validate our prototype, a series of experiments were performed on prostate phantoms. The 3D scan of the string phantom produced minimal geometric distortions, and the geometric error of the 3D imaging subsystem was 0.37 mm. The accuracy of 3D prostate segmentation was determined by comparing the known volume in a certified phantom to a reconstructed volume generated by our system and was shown to estimate the volume with less then 5% error. Biopsy needle guidance accuracy tests in agar prostate phantoms showed that the mean error was 2.1 mm and the 3D location of the biopsy core was recorded with a mean error of 1.8 mm. In this paper, we describe the mechanical design and validation of the prototype system using an in vitro prostate phantom. Preliminary results from an ongoing clinical trial show that prostate motion is small with an in-plane displacement of less than 1 mm during the biopsy procedure.
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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) | 0.001 | 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