AI Multimodal Model for Predicting CRPC Progression Risk

This study aims to develop an artificial intelligence model to predict which patients with advanced prostate cancer are at higher risk of developing castration-resistant prostate cancer (CRPC), a more severe form of the disease. The study will use pre-treatment MRI images, biopsy pathology slides, and clinical data collected from patients who received either hormone therapy (ADT) or radical prostatectomy surgery. By integrating these different types of data, the AI model is designed to help doctors identify high-risk patients earlier, personalize treatment plans, and ultimately improve patient outcomes. This is a multicenter, retrospective study that will analyze data from over 500 patients with at least 24 months of follow-up. The performance of the model will be evaluated using standard accuracy metrics.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Prostate Cancer Castration-resistant Prostate Cancer Genital Diseases Genital Diseases, Male Genital Neoplasms, Male Male Urogenital Diseases Neoplasms Neoplasms by Site Prostatic Diseases Prostatic Neoplasms Urogenital Diseases Urogenital Neoplasms

Age range

18 year–80 year

Sex eligibility

Male

Study type

Observational

Primary location

Guangxi Medical University First Affiliated Hospital

Nan'ning, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

(1) Male, age ≥18 years; (2) Pathologically confirmed newly diagnosed advanced prostate cancer; (3) Received at least 6 months of androgen deprivation therapy OR underwent radical prostatectomy; (4) Have complete baseline MRI (T2WI, DWI, ADC) and biopsy pathology data; (5) Have complete follow-up records (at least 24 months).

Exclusion criteria

(1) Missing clinical information; (2) MRI images of poor quality or missing key sequences; (3) Poor quality pathological specimens; (4) Lost to follow-up or incomplete data during follow-up; (5) Concurrent other malignant tumors; (6) Prior anti-tumor therapy.

Treatment and study plan

Primary outcomes

Prediction of CRPC Progression Risk in the ADT Treatment Group

Time frame: Minimum 24 months of follow-up

Performance of the multimodal AI model in predicting progression to castration-resistant prostate cancer in patients with newly diagnosed advanced prostate cancer who received at least 6 months of androgen deprivation therapy. Metrics include AUC, accuracy, sensitivity, and specificity.
Prediction of CRPC Progression Risk in the Radical Prostatectomy Group

Time frame: Minimum 24 months of follow-up

Performance of the multimodal AI model in predicting progression to castration-resistant prostate cancer in patients with newly diagnosed advanced prostate cancer who underwent radical prostatectomy. Metrics include AUC, accuracy, sensitivity, and specificity.

Sponsors and collaborators

Lead sponsor

Guangxi Medical University

Other

Registry information

Official study title

Artificial Intelligence for Predicting Progression Risk of Castration-Resistant Prostate Cancer by Integrating Multimodal Data: A Multicenter, Retrospective Study

Acronym: AI-MM_CPRC

Important dates

Study start: 2025
Primary completion: 2028
Study completion: 2028
First posted: Jun 22, 2026
Registry last updated: Jun 22, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Active, Not Recruiting