Micro-Ultrasound: Current Role in Prostate Cancer Diagnosis and Future Possibilities
Bibliographic record
Abstract
Prostate Cancer (PCa) is the second most common cancer in men. Population screening using prostate specific antigen (PSA) blood test and digital rectal exam (DRE) is recommended by the NCCN, EAU and other prominent clinical guidelines. While MRI is the recommended initial test in men at risk for PCa, micro-Ultrasound (MicroUS) is a novel high resolution ultrasound technology that has shown promise in PCa detection. This article provides a narrative review of the studies to date which have been conducted to evaluate the functionality and efficacy of MicroUS within the patient care pathway for prostate cancer. A total of 13 relevant publications comparing detection of csPCa between MicroUS and mpMRI were selected. An amount of 4 publications referring to use of MicroUS for other indications were found. Each publication was evaluated for risk of bias and applicability using the Quality Assessment of Diagnostic Accuracy (QUADAS-2) tool. The studies reviewed conclude that MicroUS detection rates for clinically significant prostate cancer diagnosis are comparable to the detection rates of mpMRI guided biopsy procedures. While the existing literature indicates that MicroUS should replace conventional TRUS for prostate imaging and biopsy, it is not yet clear whether MicroUS should be used on its own or in conjunction with mpMRI for augmenting prostate cancer detection. The ongoing OPTIMUM trial will provide evidence on how best to utilize this new technology. Early data also suggest this flexible new imaging modality has a place in local staging and active surveillance of prostate cancer as well as in bladder cancer staging.
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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".