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

NCT ID: NCT07111364

Last Updated: 2025-08-17

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

400 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-05-27

Study Completion Date

2026-05-31

Brief Summary

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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.

Detailed Description

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Conditions

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Deep Learning Ultrasound Bladder Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Interventions

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observational diagnostic model development

observational diagnostic model development

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Peking University First Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Department of Urology, Peking University First Hospital

Beijing, , China

Site Status RECRUITING

Countries

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China

Central Contacts

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Zheng Zhang

Role: CONTACT

+86 139 0137 1490

Facility Contacts

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Zheng Zhang

Role: primary

Other Identifiers

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BCA-AI-US

Identifier Type: -

Identifier Source: org_study_id

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