Artificial Intelligence-assisted Common Bile Duct Stent Selection in Endoscopic Retrograde Cholangiopancreatography

Endoscopic Retrograde Cholangiopancreatography Clinical Trial

Official title:

Artificial Intelligence-assisted Common Bile Duct Stent Selection in Endoscopic Retrograde Cholangiopancreatography

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05321472
• Other study ID #: 2021-SDU-QILU-090
• Status: Recruiting
• Start date: April 20, 2022
• Est. completion date: April 2023

Study information

• Verified date: May 2022
• Source: Shandong University
• Contact: Yanqing Li, MD, PhD
• Phone: 053182169385
• Email: liyanqing[@]sdu.edu.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Common bile duct stenosis is an important indication for endoscopic retrograde cholangiopancreatography(ERCP). Appropriate selection of bile duct stent size is not only conducive to successful stent implantation but also to improve the prognosis of patients. Currently, the selection of stent specifications is based on the operator's empirical estimation, which is not only not accurate but also increases the radiation exposure time, causing unnecessary harm to both the operator and the patient. Our objective is to develop an artificial intelligence algorithm to automatically select appropriate stent.

Description:

Endoscopic Retrograde Cholangiopancreatography (ERCP) is an operation with high risk. Common bile duct stone and stenosis are important indications. The quality control of ERCP is the key to improve its success rate and reduce complications, which has received great attention. In 2015, the American Society of Gastrointestinal Endoscopy/American College of Gastroenterology (ASGE/ACG) issued ERCP quality control indicators, among which biliary stent placement and radiographic fluoroscopy time are important intraoperative quality control indicators.

The selection of appropriate biliary stent size is not only conducive to successful stent implantation but also to improve the prognosis of patients. Choose a stent of appropriate length. The proximal side of the stent should be 1cm above the obstruction segment, and the distal tail should be located just outside the nipple. The length of the stent can be determined by measuring the distance between the proximal end of the obstruction and the nipple under X-ray.

Current stent size selection is based on the operator's empirical estimation :(1) estimate the distance by endoscope diameter or cone length or catheter marking; (2) By retracting the guidewire, calculate the distance of the guidewire retracting between two points to estimate the length of the stent.The long radiation exposure time results in unnecessary injuries to both the operator and the patient.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 600
• Est. completion date: April 2023
• Est. primary completion date: August 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients older than 18 years old who underwent ERCP

Exclusion Criteria:

• failed cholangiopancreatography caused by failed intubation, gastric retention, duodenal disease and so on

• patients proved no stenosis in common bile duct

• poor cholangiograms due to the lack of contrast agent or insufficient filling of contrast agent (cholangiograms without the completed CBD or thumbnails)

Related Conditions & MeSH terms

• Endoscopic Retrograde Cholangiopancreatography
• Stenosis of Bile Duct

Locations

Country	Name	City	State
China	Department of Gastroenterology,QiLu Hospital,Shandong University	Jinan	Shandong

Sponsors (1)

Lead Sponsor	Collaborator
Shandong University

Country where clinical trial is conducted

China, 

References & Publications (2)

Adler DG, Lieb JG 2nd, Cohen J, Pike IM, Park WG, Rizk MK, Sawhney MS, Scheiman JM, Shaheen NJ, Sherman S, Wani S. Quality indicators for ERCP. Gastrointest Endosc. 2015 Jan;81(1):54-66. doi: 10.1016/j.gie.2014.07.056. Epub 2014 Dec 2. Review. Erratum in: Gastrointest Endosc. 2015 Apr;81(4):1060. — View Citation

Huang L, Lu X, Huang X, Zou X, Wu L, Zhou Z, Wu D, Tang D, Chen D, Wan X, Zhu Z, Deng T, Shen L, Liu J, Zhu Y, Gong D, Chen D, Zhong Y, Liu F, Yu H. Intelligent difficulty scoring and assistance system for endoscopic extraction of common bile duct stones based on deep learning: multicenter study. Endoscopy. 2021 May;53(5):491-498. doi: 10.1055/a-1244-5698. Epub 2020 Aug 24. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The accuracy of the calculated length of the stents by the artificial intelligence	The length of the stent was calculated "the length from the stenosis to the papilla+2cm".The length of the stent selected by experts is the gold standard	6 months
Secondary	The accuracy of the segmentation of the artificial intelligence	The accuracy of the segmentation of the common bile duct, duodenoscopy and stenosis lesions by the artificial intelligence	4 months