Clinical trial · Observational
Improving Prostate Lesion Classification and Development of a PI-RADS 3 Classifier
Improving Prostate Lesion Classification and Diagnostic Accuracy Using Machine Learning: A Comprehensive Evaluation and Development of a PI-RADS 3 Classifier
NCT06116344CI-TRIAL-00071049completedClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The investigators propose an AI methodology combining machine learning, histological results and expert image interpretation for the development of a PI-RADS 3 classifier.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Prostate Cancer | Malignant Prostate Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (2)
- label
- experimental
- description
- experimental: patients with a condition
- label
- control group
- description
- control group: patients without condition
Primary outcomes (4)
- measure
- Normalized Quantitative Signal - Intensity - Measurements with Region of Interest drawn in specific T2-weighted axial MRI Images
- timeFrame
- through study completion, an average of 3 years
- description
- Regions of interest for quantitative signal intensity measurements will be drawn in various prostate lesions, the size of the region of interest will depend on the target structure. Image analysis will be performed on a PACS workstation. Signal intensity will be measured and normalized, therefore no units needed.
- measure
- Quantitative Signal - Intensity - Measurements with Region of Interest in specific in Apparent diffusion coefficient (ADC) axial MRI Images
Eligibility
Eligibility (as posted)
- Sex
- Male
- Minimum age
- 18 Years
- Maximum age
- 90 Years
Show eligibility criteria text
Inclusion Criteria: 1. Only patients with a clinical indication for mp prostate MRI will be included in this prospective study. 2. No allergies to GBCA Exclusion Criteria: 1\. Contraindications for MRI
References
Publications (3)
- RESULTWeinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2016 Jan;69(1):16-40. doi: 10.1016/j.eururo.2015.08.052. Epub 2015 Oct 1. PMID 26427566
- RESULTTurkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, Tempany CM, Choyke PL, Cornud F, Margolis DJ, Thoeny HC, Verma S, Barentsz J, Weinreb JC. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. Eur Urol. 2019 Sep;76(3):340-351. doi: 10.1016/j.eururo.2019.02.033. Epub 2019 Mar 18. PMID 30898406
- RESULTMorash C. What do you do with PI-RADS-3? Can Urol Assoc J. 2021 Apr;15(4):122. doi: 10.5489/cuaj.7262. No abstract available. PMID 33830009