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A Study on Predicting Prostate Cancer Using Artificial Intelligence-Based Integrated Analytical Techniques

Clinical Application Study of an Artificial Intelligence-Based Multimodal Data Fusion Model for Predicting Prostate Cancer in the PSA Gray Zone

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120111
Enrollment
Unknown
Registered
2026-03-09
Start date
2026-03-10
Completion date
Unknown
Last updated
2026-03-16

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

Conditions

Prostate Malignant Tumor

Interventions

Gold Standard:Prostate biopsy pathology served as the gold standard for diagnosing prostate cancer in this study.
Index test:Prostate cancer risk prediction system based on an artificial intelligence multimodal data fusion model. This system integrates MRI radiomic features, serum metabolomic features, and clin

Sponsors

Lishui Central Hospital
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
50 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age = 50 years old; 2. PSA 4–10 ng/mL; 3. mpMRI or ultrasound suggests suspicious lesions; 4. No previous prostate biopsy and no history of confirmed prostate cancer; 5. No acute urinary tract infection or catheterization in the past 2 weeks; 6. Agree to provide blood samples and sign informed consent.

Exclusion criteria

Exclusion criteria: 1. Patients with a history of other malignant tumors who received systemic treatment during the follow-up period; 2. Patients with severe cardiovascular, liver or kidney failure, or mental disorders who cannot cooperate; 3. Patients who have been taking 5a-reductase inhibitors for a long term (>3 months); 4. Patients with incomplete clinical data or key images/samples unavailable; 5. Patients whose MRI image quality is poor and cannot undergo radiomics analysis; 6. Patients who withdraw informed consent or are deemed unsuitable to continue by the researcher.

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy of the prostate cancer risk prediction model (AUC);

Countries

China

Contacts

Public ContactChen Wang

Lishui Central Hospital

782057771@qq.com+86 10 1234 5678

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 20, 2026