Poster — Thur Eve — 50: Preliminary Evaluation of Ultrasound Treatment of the Human Prostate Gland Using MRI Thermometry In Vivo
Bibliographic record
Abstract
Current radical treatments for prostate cancer can have numerous, permanent side effects including incontinence, sexual dysfunction and bowel dysfunction. The development of an effective, minimally invasive treatment with fewer side effects would enhance treatment options, particularly for younger men with low‐risk disease. MRI‐guided transurethral high intensity ultrasound therapy has been shown to have a high degree of accuracy in coagulating tissue. A real‐time feedback system in conjunction with continuous MR thermometry gives the system control over heat deposition, as demonstrated in both gel and preclincal animal models. A subvolume treatment of the gland was performed on six men with low grade prostate cancer who volunteered for the procedure prior to their scheduled radical prostatectomy. Histological measurements were performed on the surgically removed prostate to asses the accuracy of the ultrasound therapy. A spinal anaesthetic was given to the patient to limit discomfort and movement during treatment. A transurethral device fitted with four 5‐mm planar transducers operating at 8MHz delivered the treatment in a 1.5T clinical MRI system. A volume within the prostate was targeted, based on MR images, usually involving a 180° rotation of the device. Temperature uncertainty of ∼1C° was obtained and the coagulation boundary from histology agreed with the target boundary with an accuracy of 1mm ± 1.5mm. This presentation describes a preliminary study of safety and feasibility in human beings.
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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 | 0.000 | 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) | 0.005 | 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".