Checking a Computer Model That Reads Prostate MRI Scans for Cancer
Checks a computer model reading prostate MRI scans for cancer in adults.
Plain-language title generated from the registry record
Registry title: Validation of a Machine Learning Model Based on MR for the Prediction of Prostate Cancer
Key facts
- Where
- Bologna, ItalySee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults who had a prostate MRI showing at least one lesion and who need a prostate biopsy at one hospital in Bologna.
- Age
- 18 years or older
- Sex
- All sexes can join.
- Disease stage
- One or more prostate lesions scored PI-RADSv2.1 ≥ 1 on a multiparametric prostate MRI.
- Earlier treatment
- People who had earlier prostate surgery or hormone therapy cannot join.
Main reasons for not taking part
- Earlier prostate surgery or hormone therapy
- MRI images of poor quality because of artifacts, such as a hip prosthesis or movement of the endorectal probe
Read by machine on 12 November 2026.
Where in Italy
- IRCCS Azienda Ospedaliero-Universitaria di BolognaBologna, ItalyContact: Caterina Gaudiano, MDTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- IRCCS Azienda Ospedaliero-Universitaria di Bologna
- Trial code
- NCT06773598
- Record updated
- 14 January 2025
- Original description
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:Read full original descriptionShow less
Validation of a Machine Learning Model Based on Multiparametric MR for the Prediction of Clinically Significant Prostate Cancer
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:
* Specificity (SP): is the probability of a negative test result, conditioned on the individual truly being negative * Sensitivity (SN): is the probability of a positive test result, conditioned on the individual truly being positive
Inclusion: Participants aged 18 at the time of examination; Obtaining informed consent; Presence of one or more lesions classified as PI-RADSv2.1 ≥ 1 at a prostate RMmp at the IRCCS Azienda Ospedaliero-Universitaria in Bologna; Indication for TRUS biopsy by fusion technique integrated with systematic biopsy at the IRCCS Azienda Ospedaliero-Universitaria in Bologna.
Exclusion: Previous prostate surgery or hormone therapy; Technically sub-optimal investigations for the presence of artifacts (hip prosthesis, movement of the endorectal probe, etc.).