Artificial Intelligence-Based Computer-Aided Diagnosis of Prostate Cancer

Safety and Accuracy of Artificial Intelligence-aided Precision MRI Assessment for the Optimization of Prostate Biopsy in Men With Suspicion of Prostate Cancer: a Multicenter Randomized Controlled Trial.

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.

Study Overview

• Status: Recruiting
• Conditions: the Application of Artificial Intelligence in the Diagnosis of Prostate Cancer
• Intervention / Treatment: Diagnostic test: the clinical use of artificial intelligence in the diagnosis of prostate cancer

• Study Type: Observational
• Enrollment (Estimated): 2000

Contacts and Locations

Study Locations

• China
  • Nanjing, China, 210029
    • Recruiting
    • Yu-Dong Zhang
    • Contact: Yu-Dong Zhang, MD;PHD; Phone Number: 15805151704; Email: njmu_zyd@163.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 60 years to 90 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Patients ≥ 60 years of age who are clinical suspicious of prostate cancer, presenting with an elevated prostatic specific antigen and/or abnormal digital rectal examination during the study enrollment period, will be eligible for inclusion. Patients will be excluded from screening if they are: (1) <60 years of age; (2) a previous surgery, radiotherapy or drug therapy for prostate cancer (interventions for benign prostatic hyperplasia or bladder outflow obstruction were deemed acceptable); (3) incomplete mp-MRI examination or artifacts of the images.

Description

Inclusion Criteria:

• Clinical suspicious of prostate cancer, presenting with an elevated prostatic specific antigen and/or abnormal digital rectal examination

Exclusion Criteria:

• (1) <60 years of age; (2) a previous surgery, radiotherapy or drug therapy for prostate cancer (interventions for benign prostatic hyperplasia or bladder outflow obstruction were deemed acceptable); (3) incomplete mp-MRI examination or artifacts of the images.

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Prospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
The First Affiliated Hospital of Nanjing Medical University	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.
The First Affiliated Hospital of Soochow University	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
biopsy or surgery confirmed newly-diagnosed prostate cancer and clinically significant prostate cancer	Biopsy or surgery confirmed newly-diagnosed prostate cancer and clinically significant prostate cancer will serve as our primary outcome. Details of follow up and disease progression for a period of two years following mp-MRI will also be collected. For patients with no suspicious lesions on mp-MRI or biopsy-negative, follow-up prostatic specific antigen for a period of two years will also be collected.	Aug,22nd,2022-Aug,22nd,2024

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
the total reviewing time	The total reviewing time of radiologists will be measured in this aim. The reviewing time will be defined as the time from initiation of interpretating prostate mp-MRI to the time the radiologists finish reviewing and assigning a PI-RADS score.	Aug,22nd,2022-Aug,22nd,2024
surgery confirmed T and N staging of prostate cancer	surgery confirmed T and N staging of prostate cancer	Aug,22nd,2022-Aug,22nd,2024
positive rate of prostate biopsy	positive rate of prostate biopsy in each arm	Aug,22nd,2022-Aug,22nd,2024

Collaborators and Investigators

• Sponsor: The First Affiliated Hospital with Nanjing Medical University
• Collaborators: The First Affiliated Hospital of Soochow University

Study record dates

Study Major Dates

• Study Start (Actual): August 22, 2022
• Primary Completion (Estimated): August 22, 2024
• Study Completion (Estimated): August 22, 2026

Study Registration Dates

• First Submitted: August 22, 2022
• First Submitted That Met QC Criteria: August 22, 2022
• First Posted (Actual): August 24, 2022

Study Record Updates

• Last Update Posted (Actual): August 21, 2023
• Last Update Submitted That Met QC Criteria: August 17, 2023
• Last Verified: August 1, 2023

More Information

Terms related to this study

• Keywords: magnetic resonance imaging; prostate cancer; artificial intelligence
• Additional Relevant MeSH Terms: Pathologic Processes; Neoplasms; Urogenital Neoplasms; Neoplasms by Site; Genital Neoplasms, Male; Prostatic Diseases; Urogenital Diseases; Male Urogenital Diseases; Genital Diseases, Male; Genital Diseases; Prostatic Neoplasms; Disease
• Other Study ID Numbers: 2019-SR-396

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No