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Artificial Intelligence-Based Computer-Aided Diagnosis of Prostate Cancer

NCT05513638 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2023-08-21

No results posted yet for this study

Summary

One-fifth of all men will develop clinically significant prostate cancers (CsPC) in their lifetime. An estimated 268,490 new prostate cancer (PCa) cases and 34,500 deaths are expected in the United States during the year 2022, making PCa the second most common cause of cancer-related deaths in men. MRI with the Prostate Imaging Reporting and Data System (PI-RADS) is a current widely used communicative tool for both CsPC detection and guiding targeted prostate biopsy. The high level of expertise required for accurate interpretation and persistent inter-reader variability has limited consistency and it has hindered the widespread adoption of PI-RADS. Artificial intelligence (AI) shows a broad prospect for medical interpretation and triage in various challenging tasks , including the PCa detection and staging with MRI. While rapid technical advances are furthering the application of AI medical imaging, their implementation in clinical practice remains a major hurdle. Besides, the prospect of data-derived AI tool is to assist human experts rather than replace them, and whether AI can match or exceed the human experts is still a matter of debate. Therefore, despite strong potential, there is urgent need for research to better quantify the accuracy, generalizability and clinical applicability before the clinical use of an AI in a real-world clinical setting.

Conditions

  • the Application of Artificial Intelligence in the Diagnosis of Prostate Cancer

Interventions

DIAGNOSTIC_TEST

the clinical use of artificial intelligence in the diagnosis of prostate cancer

Each study site will enroll consecutive eligible patients and randomize them to either (a) a group with human-based interpretation or (b) a group with human-artificial intelligence interactive interpretation, both of which are utilized as standards of care.

Sponsors & Collaborators

  • The First Affiliated Hospital of Soochow University

    collaborator OTHER

  • The First Affiliated Hospital with Nanjing Medical University

    lead OTHER

Eligibility

Min Age
60 Years
Max Age
90 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-08-22
Primary Completion
2024-08-22
Completion
2026-08-22

Countries

  • China

Study Locations

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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 NCT05513638 on ClinicalTrials.gov