The Application of Multimodal Artificial Intelligence Systems in Prostate Cancer Diagnosis and Prognosis Analysis

NCT06589154 | Completed

• 1 other identifier: M_PCa
• Study Type: observational
• Target: 1,651
• Locations: 1 country
• Sites: 10

Brief Summary

Prostate-specific antigen (PSA) testing has limited specificity for prostate cancer diagnosis, leading to a high rate of unnecessary biopsies. This multi-center study aims to develop and validate a non-invasive, multi-modal artificial intelligence model that combines cell-free DNA (cfDNA) profiles with multi-parametric MRI (mpMRI). The primary goal is to improve the accuracy of prostate cancer detection and risk stratification, particularly for men with PSA levels in the 4-10 ng/mL "gray zone," thereby providing a robust tool to guide clinical decision-making and reduce avoidable invasive procedures.

Conditions

Healthy People; Benign Prostatic Hyperplasia; Prostate Cancer

Outcome Measures

Primary Outcomes (3)

• Sensitivity of Prostate Cancer Multimodal Model in Predicting Prostate Biopsy Pathology Outcomes (Benign or Malignant)

  Through completion of study and all data analysis which may take up to one year.

• Specificity of Prostate Cancer Multimodal Model in Predicting Prostate Biopsy Pathology Outcomes (Benign or Malignant)

  Through completion of study and all data analysis which may take up to one year.

• ROC value of Prostate Cancer Multimodal Model in Predicting Prostate Biopsy Pathology Outcomes (Benign or Malignant)

  Through completion of study and all data analysis which may take up to one year.

Secondary Outcomes (6)

• ROC value of a Prostate Cancer Multimodal Model in Predicting the Pathological Outcomes of Gleason Score Categories (≤6, 7, ≥8) in Men Underwent for Prostate Biopsy

  Through completion of study and all data analysis which may take up to one year.

• Sensitivity of a Prostate Cancer Multimodal Model in Predicting the Pathological Outcomes of Gleason Score Categories (≤6, 7, ≥8) in Men Underwent for Prostate Biopsy

  Through completion of study and all data analysis which may take up to one year.

• Specificity of a Prostate Cancer Multimodal Model in Predicting the Pathological Outcomes of Gleason Score Categories (≤6, 7, ≥8) in Men Underwent for Prostate Biopsy

  Through completion of study and all data analysis which may take up to one year.

• ROC value of a Prostate Cancer Multimodal Model in Predicting Clinically Significant Prostate Cancer (csPCa) in Men Underwent Prostate Biopsy

  Through completion of study and all data analysis which may take up to one year.

• Sensitivity of a Prostate Cancer Multimodal Model in Predicting Clinically Significant Prostate Cancer (csPCa) in Men Underwent Prostate Biopsy

  Through completion of study and all data analysis which may take up to one year.

Study Arms (3)

Discovery cohort

Participants with PSA levels \>4 ng/mL and had undergone prostatic biopsy and mpMR according to the investigators retrospectively.

Diagnostic Test: Multi-modal artificial intelligence model (BEAM)

Prospective internal validation cohort

Patients who are scheduled for prostate biopsy and mpMR, with PSA levels in the 4-10 ng/mL gray zone, will be consented and enrolled in this group prospectively.

Diagnostic Test: Multi-modal artificial intelligence model (BEAM)

Prospective external validation cohort

Patients who are scheduled for prostate biopsy and mpMR, with PSA levels in the 4-10 ng/mL gray zone, will be consented and enrolled in this group prospectively.

Diagnostic Test: Multi-modal artificial intelligence model (BEAM)

Interventions

Multi-modal artificial intelligence model (BEAM) DIAGNOSTIC_TEST

Data from mpMRI and cfDNA analysis will be integrated and processed by deep learning. The model's output will be compared against the final pathological diagnosis from the prostate biopsy to evaluate its performance.

Discovery cohort; Prospective external validation cohort; Prospective internal validation cohort

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: male
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

People who are required to undergo prostatic or pelvic magnetic resonance (MR) examination

You may qualify if:

• Men aged 18-80 years with a clinical indication for prostate or pelvic magnetic resonance (MR) examination.
• Patients with normal prostate, benign prostatic hyperplasia, or prostate cancer.
• First visit on January 1, 2014, or later.

You may not qualify if:

• Diagnosis of any other malignancy within the previous 5 years.
• Prior transurethral resection or enucleation of the prostate before imaging.
• Any condition deemed by the investigator to make the patient unsuitable for study participation.

Sponsors & Collaborators

• Shanghai Changzheng Hospital: lead
• Ningbo No. 1 Hospital: collaborator
• The First Affiliated Hospital of Soochow University: collaborator
• The First Affiliated Hospital of Guangzhou Medical University: collaborator
• Jiangsu Provincial People's Hospital: collaborator
• Cancer Institute and Hospital, Chinese Academy of Medical Sciences: collaborator
• Zhongda Hospital: collaborator
• Northern Jiangsu People's Hospital: collaborator
• Changhai Hospital: collaborator
• West China Hospital: collaborator

Study Sites (10)

Cancer Hospital, Chinese Academy of Medical Sciences

Beijing, Beijing Municipality, 100021, China

Location

The First Affiliated Hospital of Guangzhou Medical University

Guangzhou, Guangdong, 510120, China

Location

Jiangsu Provincial People's Hospita

Nanjing, Jiangsu, 210029, China

Location

Zhongda Hospital, Southeast University

Nanjing, Jiangsu, China

Location

The First Affiliated Hospital of Soochow University

Suzhou, Jiangsu, 215006, China

Location

Northern Jiangsu People's Hospita

Yangzhou, Jiangsu, 225001, China

Location

Changhai Hospital

Shanghai, Shanghai Municipality, 200433, China

Location

Shanghai Changzheng Hospital

Shanghai, Shanghai Municipality, 201209, China

Location

West China Hospital, Sichuan University

Chengdu, Sichuan, 610041, China

Location

Ningbo No. 1 Hospita

Ningbo, Zhejiang, 315010, China

Location

MeSH Terms

Conditions

Prostatic Hyperplasia; Prostatic Neoplasms

Condition Hierarchy (Ancestors)

Prostatic Diseases; Genital Diseases, Male; Genital Diseases; Urogenital Diseases; Male Urogenital Diseases; Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor, Chief of Urology

Study Record Dates

• First Submitted: September 6, 2024
• First Posted: September 19, 2024
• Study Start: October 10, 2024
• Primary Completion: July 30, 2025
• Study Completion: July 30, 2025
• Last Updated: September 2, 2025

Record last verified: 2025-08

Locations

CN (10)