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.

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.

Male patients with newly diagnosed advanced prostate cancer