MR Imaging–controlled Transurethral Ultrasound Therapy for Conformal Treatment of Prostate Tissue: Initial Feasibility in Humans
Bibliographic record
Abstract
PURPOSE: To evaluate the feasibility and safety of magnetic resonance (MR) imaging-controlled transurethral ultrasound therapy for prostate cancer in humans. MATERIALS AND METHODS: This pilot study was approved by the institutional review board and was performed in eight men (mean age, 60 years; range, 49-70 years) with localized prostate cancer (Gleason score≤7, prostate-specific antigen level #15 μg/L) immediately before radical prostatectomy. All patients provided written informed consent. This phase 0 feasibility and safety study is the first evaluation in humans. Transurethral ultrasound therapy was performed with the patient under spinal anesthesia by using a clinical 1.5-T MR unit. Patients then underwent radical prostatectomy, and the resected gland was sliced in the plane of treatment to compare the MR imaging measurements with the pattern of thermal damage. The overall procedure time and coagulation rate were measured. In addition, the spatial targeting accuracy was evaluated, as was the thermal history along the thermal damage boundaries in the gland. RESULTS: The average procedure time was 3 hours, with 2 or fewer hours spent in the MR unit. The treatment was well tolerated by all patients, and a temperature uncertainty of less than 2°C was observed in the treatments. The mean temperature and thermal dose measured along the boundary of thermal coagulation were 52.3°C±2.1 and 3457 (cumulative equivalent minutes at 43°C)±5580, respectively. The mean treatment rate was 0.5 mL/min, and a spatial targeting accuracy of -1.0 mm±2.6 was achieved. CONCLUSION: MR imaging-controlled transurethral ultrasound therapy is feasible, safe, and well tolerated. This technology could be an attractive approach for whole-gland or focal therapy.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".