NCT07111364

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

Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 400 (estimated)
• Sponsor: Peking University First Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 85 Years
• Healthy volunteers: Not accepted

Summary

This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.

Conditions

• Deep Learning
• Ultrasound
• Bladder Cancer

Interventions

Type	Name	Description
OTHER	observational diagnostic model development	observational diagnostic model development

Timeline

• Start date: 2025-05-27
• Primary completion: 2026-05-01
• Completion: 2026-05-31
• First posted: 2025-08-08
• Last updated: 2025-08-17

Locations

1 site across 1 country: China