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

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: Prostate CA
• Intervention / Treatment: Diagnostic test: Radiologist interpretation; Diagnostic test: AI (Lucida Pi) interpretation

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

• Study Contact: Name: Ng Alexander, MBBS BSc (Hons); Phone Number: +44 0207 679 5057; Email: alexander.ng@ucl.ac.uk
• Study Contact Backup: Name: PARADIGM Study Team; Email: med.paradigm@ucl.ac.uk

Participation Criteria

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

How is the study designed?

Design Details

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

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Radiologist interpretation of MRI +/- prostate biopsy; Radiologist Interpretation	Diagnostic test: Radiologist interpretation; Radiologist will interpret the prostate MRI (as per standard of care)
Experimental: AI interpretation of MRI +/- prostate biopsy; AI Interpretation	Diagnostic test: AI (Lucida Pi) 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	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	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	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.	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	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)	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)	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)	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	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	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	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	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	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

• Sponsor: University College, London
• Collaborators: Lucida Medical Ltd
• 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

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

• Keywords: MRI; Cancer; Artificial Intelligence; Prostate; AI
• Additional Relevant MeSH Terms: Neoplasms
• 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