Machine Learning Model for Prostate Cancer Prediction
Validation of a Machine Learning Model Based on MR for the Prediction of Prostate Cancer
Recruiting
Observational Study
Prostate Cancer
No Study Drug
Researchers observe your health over time — no experimental treatment is given.
At a Glance
- Age
- 18 and older
- Sex
- Any
- Study type
- Observational
- Participants needed
- 1,100 (estimated)
- Sponsor
- IRCCS Azienda Ospedaliero-Universitaria di Bologna · Other
Who this trial is looking for
This trial is looking for men aged 18 or older who have certain findings in their prostate imaging. Participants will help validate a machine learning model that predicts prostate cancer based on images taken during an MRI.
Are You a Good Fit for This Trial?
You may be able to join if
- I am 18 years old or older.
- I have agreed to take part in this study.
- I have one or more lesions classified as PI-RADSv2.1 ≥ 1.
- I need to have a specific type of biopsy using fused imaging.
You may not be able to join if
- I have had prostate surgery before.
- I have received hormone therapy for prostate cancer.
- My imaging tests were not clear due to artifacts.
Summarized in plain language from this trial's official eligibility criteria. The full criteria are further down this page — only the research team can confirm whether you qualify.
Think this trial could be right for you?
Answer a few quick questions to see if you may meet the eligibility requirements.
Check Your Eligibility
About This Trial
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 probabili…
Trial Locations
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Eligibility Criteria
Inclusion Criteria:
* 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…
Contacts