RecruitingNot ApplicableNCT06360523

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

ProstateAI - A Prospective Paired Validating Cohort Study to Evaluate an MRI-based Optimized Prostate Cancer Diagnostic Pathway Powered by Artificial Intelligence


Sponsor

Chinese University of Hong Kong

Enrollment

368 participants

Start Date

Jun 14, 2024

Study Type

INTERVENTIONAL

Conditions

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.


Eligibility

Sex: MALEMin Age: 18 Years

Inclusion Criteria4

  • Patients recommended for prostate biopsy for diagnosis or re-assessment.
  • Men at least 18 years or over
  • Patients with prostate MRI image eligible for radiologist review and AI review.
  • Patient Informed Consent is signed.

Exclusion Criteria2

  • Patient contraindicated to prostate biopsy
  • Patient failed to complete the biopsy procedure

Interventions

DIAGNOSTIC_TESTAI 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_TESTStandard review

The MRI image will be reviewed by radiologist.


Locations(1)

Prince of Wales Hospital, Chinese University of Hong Kong

Hong Kong, Hong Kong

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NCT06360523


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