Multiparametric ultrasound and micro-ultrasound in prostate cancer: a comprehensive review
Bibliographic record
Abstract
Prostate cancer (PCa) is the most common non-cutaneous cancer diagnosed in males. Traditional tools for screening and diagnosis, such as prostate-specific antigen, digital rectal examination and conventional transrectal ultrasound (TRUS), present low accuracy for PCa detection. Multiparametric MRI has become a game changer in the PCa diagnosis pathway and MRI-targeted biopsies are currently recommended for males at risk of clinically significant PCa, even in biopsy-naïve patients. Recent advances in ultrasound have also emerged with the goal to provide a readily accessible and cost-effective tool for detection of PCa. These newer techniques include elastography and contrast-enhanced ultrasound, as well as improved B-mode and Doppler techniques. These modalities can be combined to define a novel ultrasound approach, multiparametric ultrasound. High frequency Micro-ultrasound has emerged as a promising imaging technology for PCa diagnosis. Initial results have shown high sensitivity of Micro-ultrasound in detecting PCa in addition to its potential in improving the accuracy of targeted biopsies, based on targeting under real-time visualization, rather than relying on cognitive/fusion software MRI-transrectal ultrasound-guided biopsy.
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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) | 0.005 | 0.001 |
| 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 | 0.001 |
| 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".