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Recruiting

NCT Number: NCT07111364

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

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.

Recruiting

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Key information

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Department of Urology, Peking University First Hospital

Beijing, 100034, China

Location status: Recruiting

Location contact

Zheng Zhang

CONTACT

[email protected]

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

observational diagnostic model development

Other

observational diagnostic model development

Primary outcomes

  1. Overall Diagnostic Accuracy

    Time frame: From may 2025 to may 2027

Study contacts

Contact information is provided by the study sponsor or research team.

Sponsors and collaborators

Lead sponsor

Peking University First Hospital

Other

Registry information

Official study title

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

Acronym: BCA-AI-US

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Aug 8, 2025
Registry last updated
Aug 17, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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