Prostate MRI Analysis by Radiologists and Artificial Intelligence - Disease Identification and Guided Management (PARADIGM)

June 9, 2026 updated by: University College, London

A Study Assessing Whether Artificial Intelligence is Non-inferior to Radiologists in the Diagnosis of Clinically Significant Prostate Cancer.

Prostate cancer is the most common male cancer in 112 countries and makes up 7% of global cancer cases, and is the second leading cause of cancer-related deaths in men.

Normally, men with suspected prostate cancer undergo a prostate MRI, and then a Radiologist would review this scan to identify any suspicious areas for cancer within the prostate. Prostate MRI interpretation, however, is an expert skill with a steep learning curve, and internationally, there is a growing shortage of Radiologists.

The PARADIGM trial aims to assess if AI can perform just as well as Radiologists in interpretating prostate MRI scans to identify prostate cancer. Enrolled participants will undergo a prostate MRI, which is the normal method used for investigating suspected prostate cancer. AI and a Radiologist will both interpret the MRI, without knowledge of each other's interpretation. Once both reports have been made, the Radiologist will be asked to produce a third, combined report.

If there is a suspicious area in the prostate identified either by AI or the Radiologist, targeted biopsies will be performed. f there are no suspicious areas on the MRI and if you are at low risk of harbouring cancer, which occurs in about 30% of men, then no biopsy will be taken at all.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

Aim: To assess whether artificial intelligence is non-inferior to radiologists in the diagnosis of clinically significant prostate cancer on MRI.

Objectives

Primary

1. To compare the proportion of men who have clinically significant prostate cancer detected on MRI using AI ± targeted biopsy with radiologists ± targeted biopsy.

Secondary

  1. To compare the proportion of men who have clinically insignificant prostate cancer detected on MRI using AI ± targeted biopsy with radiologists ± targeted biopsy.
  2. To compare the proportion of men with non-suspicious MRIs for AI vs radiologists.
  3. To compare the proportion of men with indeterminately scored MRI as reported by AI vs radiologists.
  4. To compare the diagnostic test performance of AI vs radiologist.
  5. To compare the additive value of AI when used together with a radiologist interpretation (summative of all identified lesions) compared to a radiologist alone.
  6. To compare the additive value of AI when used together with a radiologist interpretation (where the radiologist can interact with the AI system by accepting or rejecting AI-identified lesions) compared to a radiologist alone.
  7. To determine the frequency of AI failures.
  8. To compare treatment eligibility decisions between AI and Radiologist.
  9. To compare the cost-effectiveness of unblinded AI interpreted by the radiologist compared to radiologist alone for prostate cancer detection, and AI alone vs. radiologist alone, and a 3-arm analysis considering all three.

Design:

Prospective, international, within-patient, multi-centre, level-1 evidnece trial in participants referred to hospital with a clinical suspicion of prostate cancer.

Study Type

Interventional

Enrollment (Estimated)

500

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  1. Men at least 18 years of age referred with clinical suspicion of prostate cancer
  2. Serum PSA ≤ 20 ng/mL
  3. Fit to undergo all procedures listed in the protocol
  4. Able to provide written informed consent

Exclusion Criteria:

  1. Prior prostate biopsy
  2. Prior prostate MRI on a previous encounter*
  3. Prior treatment for prostate cancer
  4. Contraindication to MRI (e.g. claustrophobia, pacemaker)
  5. Metalwork that would give rise to artefact on MRI (e.g. hip prosthesis, pelvic/spinal metalwork)
  6. Contraindication to prostate biopsy
  7. Unfit to undergo any procedures listed in protocol

    • An MRI on a previous encounter means a previous prostate MRI which has been seen by a doctor and has been used to inform patient management at the time of the original MRI.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Single Group Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Radiologist interpretation of MRI +/- prostate biopsy
Radiologist Interpretation
Radiologist will interpret the prostate MRI (as per standard of care)
Experimental: AI interpretation of MRI +/- prostate biopsy
AI Interpretation
AI algorithm that will interpretate the prostate MRI

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Proportion of men with clinically significant cancer
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of men with clinically significant cancer detected (any pattern 4 disease on any core (i.e. Gleason Grade ≥ 3+4/Gleason grade group ≥2).
When biopsy results available, at an expected average of 30 days post-biopsy

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Proportion of men with clinically insignificant cancer
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of men with clinically insignificant cancer detected (Gleason grade 3+3/Gleason grade group 1).
When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of men with non-suspicious MRIs
Time Frame: When MRI results available, at an expected average of 30 days post-MRI
Proportion of men with non-suspicious MRIs for AI vs Radiologists
When MRI results available, at an expected average of 30 days post-MRI
Proportion of MRIs with indeterminate scores.
Time Frame: When MRI results available, at an expected average of 30 days post-MRI
Proportion of men with indeterminately scored MRI as reported by AI vs radiologists
When MRI results available, at an expected average of 30 days post-MRI
Agreement between AI and Radiologist in score of suspicion
Time Frame: When MRI results available, at an expected average of 30 days post-MRI
Compare the proportion of MRIs with concordant scores between AI and Radiologist in score of suspicion
When MRI results available, at an expected average of 30 days post-MRI
Diagnostic test performance characteristics (AI versus Radiologist)
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Test performance characteristics for AI and Radiologists, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value.
When biopsy results available, at an expected average of 30 days post-biopsy
Diagnostic test performance characteristics (AI plus Radiologist)
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Test performance characteristics of AI in combination with Radiologist (summative of all identified lesions) compared to a radiologist alone, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value.
When biopsy results available, at an expected average of 30 days post-biopsy
Diagnostic test performance characteristics (AI-assisted Radiologist)
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Test performance characteristics of AI in combination with Radiologist (where the radiologist can interact with the AI system by accepting or rejecting AI-identified lesions) compared to a radiologist alone, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value.
When biopsy results available, at an expected average of 30 days post-biopsy
Significant cancer detected by peri-lesional biopsies
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of patients with significant cancer detected taking into account peri-lesional biopsies of AI and Radiologist declared lesions.
When biopsy results available, at an expected average of 30 days post-biopsy
Significant cancer detected by systematic biopsies
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of patients with significant cancer detected by systematic biopsies
When biopsy results available, at an expected average of 30 days post-biopsy
Frequency of AI failures
Time Frame: When MRI results available, at an expected average of 30 days post-MRI
Proportion of patients where AI was unable to interpret the MRI scan
When MRI results available, at an expected average of 30 days post-MRI
Treatment eligibility decisions
Time Frame: When biopsy results available, at an expected average of 30 days post-biopsy
Proportion of patients where treatment eligibility changed between AI and Radiologist
When biopsy results available, at an expected average of 30 days post-biopsy
Cost-efffectiveness
Time Frame: At an expected average of 30 days post-intervention
Cost-effectiveness of unblinded AI interpreted by the radiologist compared to radiologist alone in detecting significant prostate cancer, and AI alone vs. radiologist alone, and a 3-arm analysis considering all three.
At an expected average of 30 days post-intervention

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Collaborators

Investigators

  • Study Chair: Veeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD, Division of Surgery and Interventional Science, University College London, UK
  • Study Chair: Doug Pendse, MB ChB MD (Res) MRCS FRCR, Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2026

Primary Completion (Estimated)

January 1, 2029

Study Completion (Estimated)

January 1, 2029

Study Registration Dates

First Submitted

June 9, 2026

First Submitted That Met QC Criteria

June 9, 2026

First Posted (Actual)

June 15, 2026

Study Record Updates

Last Update Posted (Actual)

June 15, 2026

Last Update Submitted That Met QC Criteria

June 9, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 338739

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Anonymised data will be available at request for bona fide researchers with important research questions subject to approval by the study steering committee.

IPD Sharing Time Frame

Data will become available 1 year after publication of the main study results.

IPD Sharing Access Criteria

A study steering committee will review all requests for access to the data and will make decisions on whether or not to grant access to bona fide researchers based on the importance of the research question being asked, ensuring analysis is non overlapping with existing analyses and planned analyses.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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