Prostate Cancer Clinical Trial
Official title:
Improving Prostate Lesion Classification and Diagnostic Accuracy Using Machine Learning: A Comprehensive Evaluation and Development of a PI-RADS 3 Classifier
Verified date | November 2023 |
Source | Paracelsus Medical University |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The investigators propose an AI methodology combining machine learning, histological results and expert image interpretation for the development of a PI-RADS 3 classifier.
Status | Completed |
Enrollment | 173 |
Est. completion date | August 24, 2023 |
Est. primary completion date | December 31, 2020 |
Accepts healthy volunteers | No |
Gender | Male |
Age group | 18 Years to 90 Years |
Eligibility | 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 |
Country | Name | City | State |
---|---|---|---|
Germany | Department of Radiology and Nuclear Medicine, Klinikum Nuernberg, Paracelsus Medical University, Germany | Nuernberg |
Lead Sponsor | Collaborator |
---|---|
Paracelsus Medical University |
Germany,
Morash 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. — View Citation
Turkbey 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 Repo — View Citation
Weinreb 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.eur — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Normalized Quantitative Signal - Intensity - Measurements with Region of Interest drawn in specific T2-weighted axial MRI Images | 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. | through study completion, an average of 3 years | |
Primary | Quantitative Signal - Intensity - Measurements with Region of Interest in specific in Apparent diffusion coefficient (ADC) axial MRI Images | Regions of interest for signal intensity measurements will be drawn in various prostate lesions, the size of the region of interest will depend on the target structure. Signal intensity will be measured and normalized in mm2/s | through study completion, an average of 3 years | |
Primary | Quantitative Signal - Intensity - Measurements with Region of Interest in specific in high b-value (800, 1500, 4000) axial MRI Images | Regions of interest for signal intensity measurements will be drawn in various prostate lesions, the size of the region of interest will depend on the target structure. Signal intensity will be measured and normalized in mm2/s | through study completion, an average of 3 years | |
Primary | Signal - Intensity - Measurements with Region of Interest in specific dynamic contrast enhanced (DCE) MRI Images | Regions of interest for signal intensity measurements will be drawn in various prostate lesions, the size of the region of interest will depend on the target structure. Signal intensity will be measured and normalized. Image analysis will be performed on a PACS workstation. The original Time inteisity curves are transformed in relative enhancement curves. Thus, they are normalized with respect to first point in time and represent the percentage increase compared to the time before contrast arrival, no units needed. | through study completion, an average of 3 years |
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