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To Evaluate an MRI-based Optimized Prostate Cancer Diagnostic Pathway Powered by Artificial Intelligence

NCT06360523 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 368

Last updated 2025-05-06

No results posted yet for this study

Summary

It is a prospective paired-cohort study for diagnostic test evaluation. The study aim to determine the accuracy of AI review and investigate whether AI review could detect MRI visible significant cancer as effective as radiologist review. MRI image of about 368 men recommended for biopsy will be reviewed by an AI model and an experienced radiologist, respectively. AI review (index) and radiologist review (standard) will be blinded to each other, while biopsy urologists will be well-informed of the findings of both AI review and radiologist review and make personalized biopsy plan by combining both findings. The pathological results of MRI-ultrasound fusion biopsy (reference) will serve as the gold standard to assess the diagnostic accuracy.

Conditions

Interventions

DIAGNOSTIC_TEST

AI modal

The MRI image will be reviewed by radiologist and AI model(s) respectively. The urologist will combine the results of the two approaches to optimize the biopsy strategy which is expected to result in more accurate diagnosis.

DIAGNOSTIC_TEST

Standard review

The MRI image will be reviewed by radiologist.

Sponsors & Collaborators

  • Chinese University of Hong Kong

    lead OTHER

Principal Investigators

  • Peter CHIU, FRCS, PhD · Chinese University of Hong Kong

Study Design

Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
CROSSOVER

Eligibility

Min Age
18 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-06-14
Primary Completion
2027-12-31
Completion
2028-03-31

Countries

  • Hong Kong

Study Locations

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Entities

Diseases

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 NCT06360523 on ClinicalTrials.gov