Clinical value of machine learning-based ultrasound radiomics for preoperative risk prediction of gallbladder mass lesions: a multicenter study

Status

Recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2200056165

Enrollment

Unknown

Registered

2022-02-01

Start date

2022-01-18

Completion date

Unknown

Last updated

2024-08-12

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

Conditions

gallbladder mass lesions

Interventions

Gold Standard:Postoperative pathological results

Index test:Ultrasonic images, artificial intelligence method

Eligibility

Sex/Gender

All

Age

18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Surgical resection with clear pathological diagnosis; 2. Receive ultrasonic examination within 4 weeks before operation.

Exclusion criteria

Exclusion criteria: 1. Incomplete clinical information; 2. Poor ultrasonic image quality; 3. T4 stage or distant metastasis; 4. Combined with other system tumors; 5. History of abdominal surgery.

Design outcomes

Primary

Measure	Time frame
Risk prediction of gallbladder mass lesions;sensitivity;Specificity;	—

Countries

China

Contacts

Public ContactChongke Zhao

Shanghai Tenth People's Hospital

zhaochongke123@163.com+86 18800231561

Outcome results

None listed

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