Utility of preoperative 3 Tesla pelvic phased-array multiparametric magnetic resonance imaging in prediction of extracapsular extension and seminal vesicle invasion of prostate cancer and its impact on surgical margin status: Experience at a Canadian academic tertiary care centre
Bibliographic record
Abstract
INTRODUCTION: To evaluate the utility of 3 Tesla (3T) pelvic phased-array (PPA) multiparametric magnetic resonance imaging (mpMRI) to predict extracapsular extension (ECE) and seminal vesicle invasion (SVI) and its subsequent effect on radical prostatectomy (RP) surgical margin status. METHODS: A retrospective evaluation was conducted of RP patients who underwent preoperative 3T PPA mpMRI (without endorectal coil) based on clinical probability of adverse pathological features. Frequencies, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting the status of ECE and SVI were calculated. RESULTS: -weighted sequences with diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) imaging to predict ECE was 39%, 56%, 45%, and 50%, respectively, while SVI prediction was 33%, 95%, 50%, and 91%, respectively. Twelve of the 28 cases predicted as being negative for ECE had positive margins, while two of the 20 cases predicted to be positive for ECE had positive margins. Imaging predicted four cases would have SVI, yet two had positive margins, while of the 44 cases predicted as being negative for SVI, four had positive margins. CONCLUSIONS: -weighted sequences with DWI and DCE in predicting pathological ECE and SVI is of questionable benefit. These mpMRI reports may result in closer dissection of neurovascular bundles and subsequent positive surgical margins. Caution should be exercised when basing intraoperative decisions on mpMRI findings.
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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 | 0.001 |
| 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) | 0.000 | 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".