Comprehensive Evaluation of MRI-AI in Prostate Cancer Diagnosis

NCT ID: NCT06575361

Last Updated: 2025-11-25

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 365 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-01-01
• Study Completion Date: 2025-08-31

Brief Summary

The goal of this real-world prospective diagnostic study is to comprehensively evaluate the value of MRI artificial intelligence (MRI-AI) in assisting the diagnosis of prostate cancer (PCa). The main questions it aims to answer are:

Does MRI-AI promote the accurate diagnosis and treatment of prostate cancer? What's the capability of prostate MRI-AI in calculating the prostate volumn? What's the value of prostate MRI-AI assistant diagnosis system in detecting the suspicious lesions on MRI and guiding prostate targeted biopsy? What's the value of prostate MRI-AI assistant diagnosis system in predicting the pathological results of prostate targeted biopsy? Researchers will compare the cancer detection rates of suspicious lesions detected by MRI-AI and senior radiologists.

Participants will:

Receive combination of systematic biopsy and targeted biopsy.

Detailed Description

In recent years, there have been remarkable advancements in the field of artificial intelligence (AI) techniques, particularly in the medical domain. These AI techniques have demonstrated the ability to significantly enhance various medical tasks, such as tumor detection, classification, and prognosis prediction. Increasing evidence supports the ability of AI to facilitate precise diagnosis of PCa and assist in therapeutic decisions. Compared with doctors, AI has the potential to identify not only holistic tumor morphology but also task-specific and granular radiological patterns that cannot be detected by the naked eye. Therefore, AI has great potential to reduce inconsistencies between observers and improve diagnostic accuracy. Previous AI studies at our institution have developed deep learning-based AI models trained on MR images that achieve good performance in the detection and localization of clinically significant prostate cancer (csPCa). Furthermore, the trained AI algorithms were embedded into proprietary structured reporting software, and radiologists simulated their real-life work scenarios to interpret and report the PI-RADS category of each patient using this AI-based software. However, the data is mostly retrospective. The capability of detecting the suspicious lesions on MRI, guiding the prostate targeted biopsy, and optimizing the biopsy scheme warrants further investigation.

The goal of this real-world prospective diagnostic study is to comprehensively evaluate the value of MRI artificial intelligence (MRI-AI) in assisting the diagnosis of prostate cancer (PCa). The main questions it aims to answer are:

Does MRI-AI promote the accurate diagnosis and treatment of prostate cancer? What's the capability of prostate MRI-AI in calculating the prostate volumn? What's the value of prostate MRI-AI assistant diagnosis system in detecting the suspicious lesions on MRI and guiding prostate targeted biopsy? What's the value of prostate MRI-AI assistant diagnosis system in predicting the pathological results of prostate targeted biopsy? Researchers will compare the cancer detection rates of suspicious lesions detected by MRI-AI and senior radiologists.

Participants will:

Receive combination of systematic biopsy and targeted biopsy.

Conditions

Prostate Cancer

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Patients with the indication of prostate biopsy

The trained AI algorithms were embedded into proprietary structured reporting software. Before prostate biopsy, the MR images of patients were uploaded to the AI software. The prostate gland and suspicious lesions were annotated and highlighted by AI software. Urogenital radiologists who were blinded to MRI-AI reports independently reviewed the MR images, annotated the suspicious lesions. Then the urologists read both the MRI-AI reports and urogenital radiologist's reports, and conducted 3-5 core targeted biopsy (TB) at each suspicious lesion found by MRI-AI and urogenital radiologists, followed by 12 core systematic biopsy (SB).

Group Type: EXPERIMENTAL

Combination of targeted biopsy and systematic biopsy

Intervention Type: DIAGNOSTIC_TEST

Before prostate biopsy, the MR images of patients were independently reviewed by MRI-AI and urogenital radiologists. Then the images with suspicious lesions highlighted by MRI-AI and urogenital radiologists. Urologists conducted targeted biopsies for all suspicious lesions and systematic biopsies. Biopsies were performed under the guidance of transrectal ultrasound (TRUS) through the transrectal or transperineal route.

Interventions

Combination of targeted biopsy and systematic biopsy

Before prostate biopsy, the MR images of patients were independently reviewed by MRI-AI and urogenital radiologists. Then the images with suspicious lesions highlighted by MRI-AI and urogenital radiologists. Urologists conducted targeted biopsies for all suspicious lesions and systematic biopsies. Biopsies were performed under the guidance of transrectal ultrasound (TRUS) through the transrectal or transperineal route.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• The age of the patient is between 45 and 85.
• Patients with complete multiparametric magnetic resonance imaging (mpMRI) data, qualified image quality control.
• Patients were in accordance with the indication of prostate biopsy, including patients with suspicious prostate nodes found by digital rectal examination (DRE), the suspicious lesions found by transrectal ultrasound (TRUS) or MRI, total prostate-specific antigen (tPSA) >10ng/mL, tPSA 4-10ng/mL with free-to-total PSA ratio (f/tPSA) <0.16 or PSA density (PSAD) >0.15.
• Patients had no history of prior prostate surgery or biopsy.
• The PSA of patients should be ≤20 ng/mL.
• The prostate biopsy pathological results of above lesions were complete. The time interval between targeted prostate biopsy and prostate mpMRI examination should not exceed one month.
• Patients with complete clinical information.

Exclusion Criteria

• The clinicopathological information and mpMRI data was unqualified or incomplete.
• Patients had received radiotherapy, chemotherapy, androgen deprivation therapy, or surgery treatment before prostate mpMRI examination or prostate biopsy.
• Patients received prior prostate biopsy.
• Patients had contraindications to MRI or prostate biopsy.
• Patients were not in accordance with the indication of prostate biopsy.

• Minimum Eligible Age: 45 Years
• Maximum Eligible Age: 85 Years
• Eligible Sex: MALE
• Accepts Healthy Volunteers: No

Sponsors

Peking University First Hospital

OTHER

Sponsor Role: lead

Responsible Party

LIU Yi

Associate chief physician

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Yi LIU

Role: PRINCIPAL_INVESTIGATOR

Peking University First Hospital

Locations

Peking University First Hospital

Beijing, Beijing Municipality, China

Countries

China

Other Identifiers

AITB-003

Identifier Type: -

Identifier Source: org_study_id