Multimodal Imaging and Digital Pathology for Prostate Cancer Prediction

Summary

This is a multicenter observational study. A deep learning model integrated with multimodal imaging and digital pathology spatial registration is built based on preoperative multiparametric magnetic resonance imaging, transrectal ultrasound and postoperative digital pathological whole slide images. The study is designed to achieve accurate prediction of clinically significant prostate cancer and non-invasive risk stratification. Unnecessary prostate biopsy and overdiagnosis can be reduced to support the optimization of clinical diagnosis and treatment strategies.

Eligibility

Inclusion Criteria:

1. Subjects who are scheduled to undergo or have undergone prostate biopsy or radical prostatectomy.
2. Subjects who have completed standard-of-care preoperative multiparametric MRI (mpMRI) and transrectal ultrasound (TRUS) examinations.
3. Subjects with complete pathological diagnosis results available.
4. Age between 40 and 90 years.
5. Able and willing to provide written informed consent (for prospective cohort participants only).

Exclusion Criteria:

1. Prior history of pelvic radiation therapy or radical prostatectomy.
2. Incomplete or poor-quality mpMRI or TRUS images (e.g., motion artifacts, insufficient sequences).
3. Concurrent other primary malignant tumors.
4. Severe systemic diseases that may affect the evaluation of the prostate.
5. Subjects with incomplete clinical or pathological data.
6. Contraindications to MRI examination (e.g., incompatible metallic implants, severe claustrophobia).

Conditions3

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