Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study

Launched by PEKING UNIVERSITY FIRST HOSPITAL · Aug 1, 2025

Keywords

ClinConnect Summary

This clinical trial is exploring a new way to use ultrasound images and artificial intelligence (AI) to better understand and stage bladder cancer. By combining different types of ultrasound scans, the researchers are developing a computer program that can automatically identify tumor areas and determine how advanced the cancer is. This could help doctors make faster and more accurate decisions about treatment.

People who might join this study are adults who have a suspected bladder tumor found during an ultrasound and are planning to have surgery to remove the tumor. Participants need to be 18 to 85 years old and able to have abdominal or transrectal ultrasound scans. The study is not enrolling new participants right now but is ongoing. If you take part, you can expect to have ultrasound scans that will be analyzed by the AI system, and your results will help improve this new technology. It’s important to know that people who recently had bladder cancer treatments or have certain medical devices in place may not be eligible.

Gender

ALL

Eligibility criteria

• • Inclusion Criteria:① Suspected bladder mass detected by abdominal ultrasound (age ≥18 years);② Patients scheduled for surgical treatment of bladder tumors.
• Exclusion Criteria:
• • Age \>85 years;
• • Patients unable to undergo abdominal/transrectal ultrasound (e.g., uncooperative individuals, technically inadequate images);
• • History of bladder tumor surgery, radiotherapy, chemotherapy, or systemic therapy within 3 months; ④ Patients with indwelling medical devices (e.g., double-J ureteral stents, urinary catheters);
• • Failure to undergo bladder tumor surgery within 2 weeks post-ultrasound; ⑥ Non-urothelial carcinoma or pathologically unconfirmed diagnoses.