Magnetic resonance imaging-guided ultrasound ablation for prostate cancer – A contemporary review of performance
Bibliographic record
Abstract
Prostate cancer (PCa) is one of the most common malignancies in men, but patient outcomes are varied depending on extent of disease. Radical, whole-gland therapies, such as prostatectomy or radiotherapy, are definitive treatments for PCa, but they are associated with significant morbidity, including erectile dysfunction and urinary incontinence. Focal therapies for PCa, whereby the part of gland harboring disease is selectively treated, spares the normal surrounding structures, and minimizes the morbidity associated with whole gland treatment. The use of magnetic resonance imaging (MRI) guidance provides advantages over ultrasound guidance, such as better localization and targeting of clinically significant PCa (csPCa), as well as MRI thermometry which optimizes tissue ablation temperatures. This review will discuss two MRI-guided high-intensity focused ultrasound (HIFU) techniques - transrectal MR-guided focused ultrasound (MRgFUS) and TULSA (transurethral ultrasound ablation) ablation for localized PCa. Overall, recent major trials for MRgFUS and TULSA have shown promising oncological and functional results in the treatment of low- to intermediate-risk PCa. Recent Phase II MRgFUS trials have shown better oncologic outcomes than the published results for focal ultrasound guided HIFU and may justify the additional costs associated with MRI guidance. While initial studies on TULSA have focused on subtotal gland ablation, recent trials assessing oncological outcomes for focal treatment of angular sectors have shown promise.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".