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Prediction of Prostate Cancer and Its Invasiveness Based on Magnetic Resonance Imaging Radiomics and Deep Learning of Whole Slide Imaging:A Single-center, Single-arm, Prospective, Non-interventional Study

Prediction of Prostate Cancer and Its Invasiveness Based on Magnetic Resonance Imaging Radiomics and Deep Learning of Whole Slide Imaging:A Single-center, Single-arm, Prospective, Non-interventional Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105550
Enrollment
Unknown
Registered
2025-07-07
Start date
2025-07-15
Completion date
Unknown
Last updated
2025-07-14

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:Pathological analysis of the radical resection specimen is performed to determine the tumor area and Gleason score.
Index test:Combined magnetic resonance radiomics and deep learning technology of full-field digital slices

Sponsors

The Second Hospital of Tianjin Medical University
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
40 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Male patients aged 40-80 years 2. Newly diagnosed with prostate cancer, ??without prior antitumor therapy?? (e.g., chemotherapy, radiotherapy, or surgery) 3. Completion of ??3.0T multiparametric prostate MRI?? (including DWI, DCE, T2WI sequences) 4. Scheduled for ??radical prostatectomy?? 5. Provision of ??signed informed consent?

Exclusion criteria

Exclusion criteria: 1. History of prior prostate surgery/radiotherapy?? 2. ??Concomitant other pelvic malignancies?? 3. ??Substandard quality of whole-mount pathological sections?? 4. ??MRI contraindications or non-diagnostic image quality?? 5. ??Incomplete clinical data?

Design outcomes

Primary

MeasureTime frame
Area Under the Receiver Operating Characteristic Curve;Sensitivity;Specificity;Positive predictive value;Negative predictive value;F1 score;

Countries

China

Contacts

Public ContactZihao Liu

The Second Hospital of Tianjin Medical University

liuzihao0613@tmu.edu.cn+86 157 1250 1311

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026