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Automated bladder segmentation and urinary risk prediction using bladder margin characteristics

Automated bladder segmentation and urinary risk prediction using bladder margin characteristics

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104252
Enrollment
Unknown
Registered
2025-06-13
Start date
2025-05-16
Completion date
Unknown
Last updated
2025-06-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Neurogenic Bladder

Interventions

Observation group:None

Sponsors

China Rehabilitation Research Center
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.Patient type: Patients initially diagnosed with lower urinary tract dysfunction (LUTD); 2.Examination requirement: Underwent video urodynamic studies (VUDS) at the Urology and Pelvic Floor Rehabilitation Center of China Rehabilitation Research Center between 2016 and 2024; 3.Data completeness: Complete medical records with no missing clinical data.

Exclusion criteria

Exclusion criteria: 1.Interference from prior treatments: Received therapies that may affect lower urinary tract function, including anticholinergic medication use, bladder augmentation surgery, or intravesical botulinum toxin injections; 2.Comorbid conditions: Presence of bladder tumors or bladder stones; 3.Incomplete data: Cases with missing medical history or incomplete clinical records.

Design outcomes

Primary

MeasureTime frame
area under the curve of the model;—

Secondary

MeasureTime frame
decision curve analysis of the model;—

Countries

China

Contacts

Public ContactZhou Zhonghan

China Rehabilitation Research Center

zhouzhonghan94@mail.sdu.edu.cn+86 157 6423 5547

Outcome results

None listed

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