AI model using prostate MRI and PSMA PET scans to help diagnose prostate cancer
Develops an AI tool to diagnose prostate cancer from two types of scans in men.
Plain-language title generated from the registry record
Registry title: Development and Validation of a Non-Invasive AI Diagnostic Model for Prostate Cancer Using Multiparametric MRI and PSMA PET/CT
Key facts
- Where
- Beijing, Guangzhou, Jinan, and Shanghai, ChinaSee the 5 sites
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adult men who had both a prostate MRI and a PSMA PET/CT scan before treatment, with a prostate biopsy or surgery result on file.
- Age
- 18 years or older
- Sex
- Men only
- Disease stage
- Prostate cancer diagnosis confirmed by prostate biopsy or radical prostatectomy (pathology result needed). The record also asks for PSA levels in the gray zone of 4-20 ng/mL in part of the analysis.
- Earlier treatment
- Scans must have been done before systemic treatment or radical prostatectomy. People with earlier prostate surgery (for example TURP), hormone therapy or radiotherapy cannot join.
- Biomarker or test result
- Complete data are needed: PSA (tPSA, fPSA), TNM stage, Gleason score, PI-RADS score, SUVmax, prostate volume, age and BMI. Original scan files (DICOM) must be available.
Main reasons for not taking part
- History of another cancer
- Earlier prostate surgery (for example TURP)
- Earlier hormone therapy or radiotherapy
- Severe kidney problems
- Major organ failure or life expectancy under 1 year
Read by machine on 12 November 2026.
Where in China
- Beijing HospitalBeijing, ChinaNo longer taking part
- Chinese PLA General HospitalBeijing, ChinaNo longer taking part
- The First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou, ChinaNo longer taking part
- Qilu Hospital of Shandong UniversityJinan, ChinaNo longer taking part
- Renji Hospital Shanghai Jiao Tong University School of MedicineShanghai, ChinaNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- Xiangya Hospital of Central South University
- Trial code
- NCT07690306
- Record updated
- 15 September 2026
- Original description
Prostate cancer is one of the most common malignancies in men. Currently, due to the limited diagnostic accuracy of existing imaging tests, there is a risk of missed diagnosis or unnecessary prostate biopsy. This study aims to develop and validate a non-invasive artificial intelligence (AI) diagnostic model using two advanced imaging techniques: multiparametric MRI (mpMRI) and PSMA PET/CT. By integrating information from both imaging modalities, the AI model is expected to improve the diagnostic accuracy of prostate cancer, reduce unnecessary biopsies, and assist physicians in making better clinical decisions. This is a retrospective, multicenter study that plans to collect imaging and pathology data from approximately 1,000 to 1,500 patients across six major hospitals in China. The diagnostic performance of the model will be evaluated, including its ability to identify clinically significant prostate cancer and its value in assisting diagnosis in patients with PSA levels in the gray zone (4-20 ng/mL).Read full original descriptionShow less
A Retrospective, Multicenter Study to Develop and Validate a Non-Invasive Artificial Intelligence Diagnostic Model for Prostate Cancer Using Multiparametric MRI and PSMA PET/CT, With Pathologically Confirmed Diagnosis as the Reference Standard
Prostate cancer is one of the most common malignancies in men. Currently, due to the limited diagnostic accuracy of existing imaging tests, there is a risk of missed diagnosis or unnecessary prostate biopsy. This study aims to develop and validate a non-invasive artificial intelligence (AI) diagnostic model using two advanced imaging techniques: multiparametric MRI (mpMRI) and PSMA PET/CT. By integrating information from both imaging modalities, the AI model is expected to improve the diagnostic accuracy of prostate cancer, reduce unnecessary biopsies, and assist physicians in making better clinical decisions. This is a retrospective, multicenter study that plans to collect imaging and pathology data from approximately 1,000 to 1,500 patients across six major hospitals in China. The diagnostic performance of the model will be evaluated, including its ability to identify clinically significant prostate cancer and its value in assisting diagnosis in patients with PSA levels in the gray zone (4-20 ng/mL).
Inclusion: Age ≥ 18 years; ECOG performance status 0-2; Life expectancy > 6 months; Underwent mpMRI and PSMA PET/CT before systemic treatment or radical prostatectomy, with original DICOM data available for export; Has pathological diagnosis from prostate biopsy or radical prostatectomy as the gold standard; Complete clinical data available, including pre-treatment PSA (tPSA, fPSA), TNM stage, Gleason score, PI-RADS score, SUVmax, prostate volume (from MRI/PSMA PET), age, and BMI; Informed consent for data use for research purposes according to each center's ethics requirements.
Exclusion: Previous prostate surgery (e.g., TURP); Prior endocrine therapy or radiotherapy; History of other malignant tumors; Severe renal insufficiency; Major organ dysfunction or life expectancy < 1 year.