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Not Yet Recruiting NCT07631806

Intelligent Screening and Precision Diagnosis of Prostate Cancer Based on Multimodal Data

Conditions: Prostate Cancer With PSA Gray Zone

Sex: Male
Ages: 45 Years – N/A
Healthy volunteers: Yes
Enrollment: 500
Sponsor: Guangxi Medical University

Summary

This project aims to develop a precision screening and diagnostic solution for prostate cancer based on multimodal artificial intelligence, focusing on addressing the diagnostic challenge in patients within the PSA "gray zone" of 4-10 ng/mL. The project will integrate multidimensional information including ctDNA liquid biopsy, routine laboratory data, and prostate ultrasound images to develop three models: a ctDNA-based multimodal AI prediction model, a routine laboratory data-assisted decision model, and an ultrasound image AI-assisted diagnostic model. On this basis, a multimodal AI fusion decision system will be established to automatically generate individualized risk assessment reports and diagnostic recommendations. Additionally, a closed-loop mechanism of "clinical use - data feedback - model optimization" will be constructed to continuously iterate model parameters using pathological gold standards, thereby improving predictive accuracy in our hospital population. The project will form a generalizable precision diagnostic workflow, reduce unnecessary biopsies in "gray zone" patients, and provide an implementable in-hospital solution for precision medicine in prostate cancer.

Eligibility Criteria

Inclusion Criteria: 1. Age ≥45 years, male 2. Presenting with abnormal serum PSA (≥4 ng/mL), abnormal digital rectal examination, or suspicious lesions on prostate ultrasound 3. Undergoing prostate biopsy with definitive pathological results 4. Signed informed consent Exclusion Criteria: 1. Previously diagnosed with prostate cancer and receiving surgery, radiotherapy, or endocrine therapy 2. With other malignancies 3. Critical missing clinical data (e.g., missing PSA value, incomplete ultrasound report)

Interested in this study? View the official listing for contact and enrollment details.

View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT07631806). StuddyBuddy aggregates publicly available trial information.