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Development of a Machine Learning–Based Predictive Model for Surgical Difficulty in Laparoscopic Cholecystectomy Using Preoperative Magnetic Resonance Cholangiopancreatography

Development of a Machine Learning–Based Predictive Model for Surgical Difficulty in Laparoscopic Cholecystectomy Using Preoperative Magnetic Resonance Cholangiopancreatography

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600123437
Enrollment
Unknown
Registered
2026-04-27
Start date
2026-04-30
Completion date
Unknown
Last updated
2026-05-04

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

Conditions

Cholelithiasis, Cholecystitis

Interventions

Observation group:None

Sponsors

Xinzhou People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. MRCP performed within 48 hours prior to surgery; 2. Complete clinical, imaging, and surgical data available.

Exclusion criteria

Exclusion criteria: 1. Suspected gallbladder carcinoma or other biliary malignancies preoperatively, or confirmed intraoperatively; 2. Concomitant intrahepatic bile duct stones or requirement for common bile duct exploration; 3. Contraindications to MRCP (e.g., severe claustrophobia, metallic implants); 4. History of prior upper abdominal surgery (e.g., subtotal gastrectomy, hepatectomy).

Design outcomes

Primary

MeasureTime frame
MRCP-based imaging features;—

Countries

China

Contacts

Public ContactZhang Feng

Xinzhou People's Hospital

zhangfengxinzhou@qq.com+86 139 3501 0271

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 7, 2026