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Prospective Validation of a Multimodal Artificial Intelligence-Assisted Diagnostic Model for Prostate Cancer

Prospective Validation of a Multimodal Artificial Intelligence-Assisted Diagnostic Model for Prostate Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600128914
Enrollment
Unknown
Registered
2026-07-28
Start date
2026-08-01
Completion date
Unknown
Last updated
2026-08-03

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

Conditions

Prostate cancer

Interventions

Gold Standard:Pathology of prostate
Index test:Multimodal Artificial Intelligence-AssistedDiagnostic Model for Prostate Cance

Sponsors

The First Affiliated Hospital of Soochow University
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
40 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age >= 40 years, with suspected prostate cancer requiring imaging evaluation and/or biopsy evaluation; 2.Scheduled to complete prostate multiparametric MRI (mpMRI) and PSMA PET/CT examinations within 4 weeks after enrollment; 3.Expected to obtain pathological gold standard results (systematic biopsy and/or targeted biopsy and/or radical prostatectomy pathology); 4.Clinical data expected to be complete (including age, PSA, PI-RADS score, etc.); 5.Voluntary participation with signed informed consent;

Exclusion criteria

Exclusion criteria: 1.Imaging examinations cannot be completed as planned or image quality does not meet diagnostic requirements; 2.Prior prostate surgery (e.g., TURP), radical radiotherapy, or endocrine therapy; 3.Concurrent other pelvic malignancies; 4.Inability to understand the informed consent form or unwillingness to sign; 5.Other conditions deemed by the investigator as rendering the patient unsuitable for participation;

Design outcomes

Primary

MeasureTime frame
Diagnostic performance of the AI model for benign vs. malignant prostate cancer detection;Predictive performance of the AI model for ISUP Grade Group classification;Diagnostic performance of the AI model for clinically significant prostate cancer (csPCa) identification;

Secondary

MeasureTime frame
Clinical value of AI-assisted diagnosis in reducing unnecessary biopsies;Basic classification performance metrics of the AI model;Comparison of AI-assisted diagnosis vs. independent radiologist diagnosis;

Countries

China

Contacts

Public ContactHuang Yuhua

The First Affiliated Hospital of Soochow University

sdfyyhyh@163.com+86 512 67975887

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Aug 10, 2026