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

NCT07647445 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 500

Last updated 2026-06-30

No results posted yet for this study

Summary

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 interpreting 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. If 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.

Conditions

  • Prostate CA

Interventions

DIAGNOSTIC_TEST

AI (Lucida Pi) interpretation

AI algorithm that will interpretate the prostate MRI

DIAGNOSTIC_TEST

Radiologist interpretation

Radiologist will interpret the prostate MRI (as per standard of care)

Sponsors & Collaborators

  • Lucida Medical Ltd

    collaborator UNKNOWN

  • University College, London

    lead OTHER

Principal Investigators

  • Veeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD · Division of Surgery and Interventional Science, University College London, UK

  • Doug Pendse, MB ChB MD (Res) MRCS FRCR · Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-10-31
Primary Completion
2029-01-31
Completion
2029-01-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07647445 on ClinicalTrials.gov