Comparison of Micro-US and Multiparametric MRI for Prostate Cancer Detection in Biopsy-Naive Men
Bibliographic record
Abstract
Background Multiparametric MRI has led to increased detection of clinically significant prostate cancer (csPCa). Micro-US is being investigated for csPCa detection. Purpose To compare multiparametric MRI and micro-US in detecting csPCa (grade group ≥2) and to determine the proportion of MRI nodules visible at micro-US for real-time targeted biopsy. Materials and methods This prospective, single-center trial enrolled biopsy-naive men with suspected prostate cancer (PCa) between May 2019 and September 2020. All patients underwent multiparametric MRI followed by micro-US; findings at both were interpreted in a blinded fashion, followed by targeted biopsy and nontargeted systematic biopsy using micro-US. Proportions were compared using the exact McNemar test. The differences in proportions were calculated. Results Ninety-four men (median age, 61 years; IQR, 57–68 years) were included. MRI- and micro-US–targeted biopsy depicted csPCa in 37 (39%) and 33 (35%) of the 94 men, respectively (P = .22); clinically insignificant PCa in 14 (15%) and 15 (16%) (P > .99); and cribriform and/or intraductal PCa in 14 (15%) and 13 (14%) (P > .99). The MRI- plus micro-US–targeted biopsy pathway depicted csPCa in 38 of the 94 (40%) men. The addition of nontargeted systematic biopsy to MRI- plus micro-US–targeted biopsy did not enable identification of any additional men with csPCa but did help identify nine additional men with clinically insignificant PCa (P = .04). Biopsy was avoided in 32 of the 94 men (34%) with MRI and nine of the 94 men (10%) with micro-US (P < .001). Among 93 MRI targets, 62 (67%) were prospectively visible at micro-US. Conclusion MRI and micro-US showed similar rates of prostate cancer detection, but more biopsies were avoided with the MRI pathway than with micro-US, with no benefit of adding nontargeted systematic biopsy to the MRI- plus micro-US–targeted biopsy pathway. Most MRI lesions were prospectively visible at micro-US, allowing real-time targeted biopsy. ClinicalTrials.gov registration no.: NCT03938376 © RSNA, 2022 Online supplemental material is available for this article.
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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) | 0.000 | 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".