Prostate Cancer: Gadolinium-enhanced MR Imaging at 3 Weeks Compared with Needle Biopsy at 6 Months after Cryoablation
Bibliographic record
Abstract
PURPOSE: To determine if nonenhancing tissue on gadolinium-enhanced magnetic resonance (MR) images obtained 3 weeks after cryoablation of the prostate helps reliably and accurately predict nonviable cryoablated tissue at 6-month biopsy. MATERIALS AND METHODS: Fifty-four consecutive patients with prostate cancer who underwent cryoablation were followed up prospectively. Fifty-one underwent gadolinium-enhanced MR imaging at 3 weeks (three had gadolinium allergy); 49, biopsy at 6 months (three refused and two had other primary malignancies); and all, prostate-specific antigen (PSA) tests at 6 weeks, 3 months, and every 3 months thereafter. MR images were evaluated and scored according to the degree of signal void and were correlated with the 6-month biopsy reports and, to a lesser degree, PSA levels. The biopsy reports were examined for the presence or absence of cancerous tissue, viable tissue, and nonviable tissue. A one-way analysis of variance was used for statistical and regression analyses. RESULTS: The correlation of MR imaging scores with PSA levels and MR imaging scores with biopsy findings resulted in P values of.337 and.780, respectively. A slight statistically significant trend existed for the relation of biopsy results with PSA levels, with a P value of.041, which was expected. CONCLUSION: Findings of postoperative gadolinium-enhanced MR imaging are not predictive of 6-month biopsy results or follow-up PSA levels.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".