False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance
Why this work is in the frame
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Bibliographic record
Abstract
MP-MRI is a critical component in active surveillance (AS) of prostate cancer (PCa) because of a high negative predictive value for clinically significant tumours. This review illustrates pitfalls of MP-MRI and how to recognise and avoid them. The anterior fibromuscular stroma and central zone are low signal on T2W-MRI/apparent diffusion coefficient (ADC), resembling PCa. Location, progressive enhancement and low signal on b ≥1000 mm²/s echo-planar images (EPI) are differentiating features. BPH can mimic PCa. Glandular BPH shows increased T2W/ADC signal, cystic change and progressive enhancement; however, stromal BPH resembles transition zone (TZ) PCa. A rounded morphology, low T2 signal capsule and posterior/superior location favour stromal BPH. Acute/chronic prostatitis mimics PCa at MP-MRI, with differentiation mainly on clinical grounds. Visual analysis of diffusion-weighted MRI must include EPI and appropriate windowing of ADC. Quantitative ADC analysis is limited by lack of standardization; the ADC ratio and ADC histogram analysis are alternatives to mean values. DCE lacks standardisation and has limited utility in the TZ, where T2W/DWI are favoured. Targeted TRUS-guided biopsies of MR-detected lesions are challenging. Lesions detected on MP-MRI may not be perfectly targeted with TRUS and this must be considered when faced with a suspicious lesion on MP-MRI and a negative targeted TRUS biopsy histopathological result. KEYPOINTS: • Multi-parametric MRI plays a critical role in prostate cancer active surveillance. • Low T2W signal intensity structures appear dark on ADC, potentially simulating cancer. • Stromal BPH mimics cancer at DWI and DCE. • Long b value trace EPI should be reviewed • Targeted biopsy of MR-detected lesions using TRUS guidance may be challenging.
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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 | 0.001 |
| 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 it