Role of multiparametric MRI in long-term surveillance following focal laser ablation of prostate cancer
Bibliographic record
Abstract
OBJECTIVE: Determine the multiparametric magnetic resonance imaging (mpMRI) appearance of the prostate following focal laser ablation (FLA) for PCa and to identify imaging characteristics associated with recurrent disease. METHODS: -weighted, dynamic contrast enhanced (DCE) and diffusion weighted imaging (DWI) appearances and also compared to corresponding PSA values and biopsy results. RESULTS: 55 cancers were treated in 54 men (mean age 61.0 years). Early mpMRI was performed in 30 (54.5%) patients while late follow-up mpMRI in 42 (84%). Ill-defined scarring with and without atrophy at the treatment site were the most common appearances. In patients with paired MRI and biopsy, one of four patients with clinically significant PCa on biopsy (≥GG2 or≥6 mm GG1) showed hyperenhancement or restricted diffusion at early follow-up. At late follow-up, positive biopsies were seen in 5/8 (63%) cases with hyperenhancement and 5/6 (83%) cases with restricted diffusion at the treatment site. PSA change was not associated with biopsy results at either time point. CONCLUSION: mpMRI is able to document the morphological and temporal changes following focal therapy. It has limited ability to detect recurrent disease in early months following treatment. Late-term mpMRI is sensitive at identifying patients with recurrent disease. Small sample size is, however, a limitation of the study. ADVANCES IN KNOWLEDGE: Implementing MRI in follow-up after FT may be useful in predicting residual or recurrent PCa and therefore provide reliable outcome data.
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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 | 0.000 | 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 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".