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Development and validation of an artificial intelligence platform for duodenal papilla detection and biliary intubation trajectory prediction during ERCP

Development and validation of an artificial intelligence platform for duodenal papilla detection and biliary intubation trajectory prediction during ERCP ——A multicenter, cross-sectional study

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400087071
Enrollment
Unknown
Registered
2024-07-18
Start date
2024-07-19
Completion date
Unknown
Last updated
2024-07-22

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

Conditions

ERCP

Interventions

Gold Standard:Endoscopic diagnosis by endoscopists
Index test:Artificial intelligence assisted endoscopic diagnosis

Sponsors

Department of Gastroenterology, Zhujiang Hospital, Southern Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: 1.Age 18 years and above, any gender. 2.Meets indications for ERCP and scheduled for the procedure. 3.No history of sphincterotomy. 4.Voluntary participation in this clinical trial, with signed informed consent form.

Exclusion criteria

Exclusion criteria: 1.Pancreatic-related surgery (e.g., requiring pancreatic duct manipulation). 2.Presence of diverticula around the type 1 papilla, making papilla classification and cannulation difficult. 3.Tumor involving the duodenal papilla. 4.Difficulty in cannulation due to other reasons (such as duodenal mucosal swelling, papillary deformity, papillary surface ulceration, etc.). 5..Anatomical changes after surgical procedures (duodenum, pancreas, biliary tract) or anomalies in pancreaticobiliary confluence. 6.Concurrent pancreatic, biliary, or duodenal tumors. 7.Other conditions deemed unsuitable for participation in this clinical trial by the investigator.

Design outcomes

Primary

MeasureTime frame
The angle deviation between the predicted bile duct cannulation trajectory by the artificial intelligence model and the actual cannulation angle.;

Secondary

MeasureTime frame
The accuracy of artificial intelligence models in detecting the duodenal papilla;Diagnostic sensibility;Diagnostic Specificity;Positive predictive value;Negative predictive value;Diagnostic relevance;Diagnosis and treatment quality control indicators;The area under the ROC curve;

Countries

China

Contacts

Public ContactWang xinying

Department of Gastroenterology, Zhujiang Hospital, Southern Medical University

xinyingwang06@163.com+86 137 2675 4880

Outcome results

None listed

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