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Construction and Validation of an MRI-Based Artificial Intelligence Model for Predicting Prostate Cancer Pathological Microenvironment Subtypes: A Multi-Center, Retrospective-Prospecive Clinical Study

Construction and Validation of an MRI-Based Artificial Intelligence Model for Predicting Prostate Cancer Pathological Microenvironment Subtypes: A Multi-Center, Retrospective-Prospecive Clinical Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500101475
Enrollment
Unknown
Registered
2025-04-25
Start date
2025-06-01
Completion date
Unknown
Last updated
2025-04-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Prostate cancer

Interventions

Case series:NA

Sponsors

the Third Affiliated Hospital of Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. The retrospective study includes patients (approximately 1,500 cases) diagnosed with prostate cancer through biopsy or radical surgery at the Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, and Yan'an Hospital of Kunming Medical University between 2014 and 2024. 2. The prospective validation includes patients (approximately 300 cases) diagnosed with prostate cancer through biopsy or radical surgery at the Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, and Yan'an Hospital of Kunming Medical University between 2025 and 2026. 3. Preoperative multiparametric MR DICOM images are available. 4. Postoperative pathological HE-stained slides are available. 5. Complete clinical and follow-up information is available.

Exclusion criteria

Exclusion criteria: 1. Presence of other malignant tumors 2. Unclear MR images or difficult-to-interpret images 3. Poor quality of preoperative H&E slides, such as tissue fading or dissolution

Design outcomes

Primary

MeasureTime frame
Pathological Microenvironment Subtypes;Overall Survival;Progression-Free Survival;ROC curve;AUC value;accuracy;Sensitivity;specificity;

Countries

China

Contacts

Public ContactYun Luo

the Third Affiliated Hospital of Sun Yat-sen University

luoyun8@mail.sysu.edu.cn+86 20 8217 9729

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026