Case ‒ Foamy high-grade prostatic intraepithelial neoplasia: A false positive for prostate cancer on multiparametric magnetic resonance imaging?
Bibliographic record
Abstract
The introduction of multiparametric magnetic resonance imaging (mpMRI) of the prostate, and specifically the introduction of diffusion-weighted imaging (DWI), has significantly impacted the diagnosis of prostate cancer and the management of clinically localized prostate cancer. Indeed, its localizing ability has now opened up opportunities to target focal lesions in partial gland ablation therapy as a treatment option for localized prostate cancer. With negative predictive rates of mpMRI approaching 90% in certain series,1 mpMRI has the ability to discriminate between clinically significant intermediate-to-high-risk prostate cancer and low-risk indolent disease. However, false positives can occur. In recent studies, lesions observed on MRI were classified as tumour on targeted biopsy in 47.6% to over 94% for tumours larger than 0.5 ml in volume.2,3 Herein, we present a case of a rare non-cancer, but putatively pre-malignant prostatic histology that was found on biopsies directed at a category 5 Prostate Imaging Reporting and Data System (PIRADS) v2 lesion.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".