An observational study in Prostate Cancer, sponsored by IRCCS Azienda Ospedaliero-Universitaria di Bologna. Recruiting at 1 site in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-01-14.
Sponsored by IRCCS Azienda Ospedaliero-Universitaria di Bologna · Observational
The goal of this observational study is to validate a clinically significant predictive machine learning model based on the processing of images RMmp (Multiparametric Magnetic Resonance Imaging). To be validated the model should be evaluated on:
This is a transversal, non-interventional observation study that involves the analysis of data collected both retrospectively and prospectively.
Patients will be enrolled by the radiologist medical staff designated by the Principal Investigator. The Principal Investigator and his delegates will be responsible for the acquisition and pseudo-anonymization of images of patients enrolled (both retrospectively and prospectively) from the RIS-PACS of the IRCCS Bologna University Hospital, Policlinico di Sant'Orsola. When available, for the participants undergoing prostate surgery, the O.U. of Pathological Anatomy will provide digital scans of the prostatic macrosections.
For the validation of the machine learning model of clinically significant CaP, a tool will be made available to radiologists. This tool is developed by the Department of Informatics - Science and Engineering, DISI, University of Bologna and Alma Mater Research Institute on Global Challenges and Climate Change, Alma Climate, University of Bologna, and integrated in an open-source Dicom viewer, Aliza MS Dicom Viewer. The doctors will then have the possibility to carry out independently the segmentation of the ADC sequences (previously pseudo-anonymized) and start the radiomic process to obtain a predictive value of the probability that the segmented lesion is clinically significant. This probability value will be calculated by the software on the basis of the machine learning model developed in PROSTATE_01. The tool also allows data collection (organized and pseudo-anonymous). The validation of the clinically significant predictive model of CaP will be carried out on all patients enrolled both retrospectively and prospectively, excluding those used in the model training phase in PROSTATE_01. After having evaluated the performance of the validated model and the effects of selection bias, once the recruitment is completed both retrospectively and prospectively, a refinement of the previously developed model will be carried out. This will be a "re-training" of the model itself, performed on training and test datasets randomly selected from the entire enrolled population from which it will be obtained randomly, by difference, also the subset for a new validation.
6,484 studies on the registry are indexed under Prostatic Neoplasms; 1,415 are open to participants now.
This study's planned enrollment of 1,100 is above the median of 200 across 1,200 observational studies indexed under Prostatic Neoplasms.
Browse Prostatic Neoplasms studies →IRCCS Azienda Ospedaliero-Universitaria di Bologna is the lead sponsor of 509 studies on the registry; 285 are open to participants now.
Counted across the registry records on this site, refreshed daily.
The study will include participants who have performed an MMR at the U.O.C. Radiology Addomino-Pelvic Diagnostic and Interventional of the IRCCS University Hospital of Bologna, Sant'Orsola Polyclinic and a TRUS biopsy with fusion technique with RMmp of the prostate. The retrospective enrollment refers to the period between 15 September 2015 (date start of TRUS biopsy with fusion technique with RMmp at the Policlinico di Sant'Orsola) and the date of approval of this study. The prospective enrollment refers to the period of time from the study approval until the following 3 years.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Specificity (SP)
Specificity is the probability of obtaining a negative classification or that the disease is indeed absent.
Time frame: From enrollment to the end of treatment at 5 years
Sensitivity (SN)
Sensitivity is the probability of a positive classification or that the disease is actually present.
Time frame: From enrollment to the end of treatment at 5 years
Positive Predictive Value (PPV)
It is the ratio of patients truly diagnosed as positive to all those who had positive test results (including healthy subjects who were incorrectly diagnosed as patient).
Time frame: From enrollment to the end of treatment at 5 years
Negative Predictive Value (NPV)
It is the ratio of subjects truly diagnosed as negative to all those who had negative test results (including patients who were incorrectly diagnosed as healthy).
Time frame: From enrollment to the end of treatment at 5 years
Eligibility is decided by the study team. Share this record with your doctor or contact the team directly.
Contact study teamGet an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
IRCCS Azienda Ospedaliero-Universitaria di Bologna →