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

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

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05321472
Enrollment
600
Registered
2022-04-11
Start date
2022-04-20
Completion date
2023-04-30
Last updated
2022-07-06

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

Conditions

Endoscopic Retrograde Cholangiopancreatography, Stenosis of Bile Duct

Brief 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.

Detailed 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.

Interventions

None listed

Sponsors

Shandong University
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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)

Design outcomes

Primary

MeasureTime frameDescription
The accuracy of the calculated length of the stents by the artificial intelligence6 monthsThe 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

Secondary

MeasureTime frameDescription
The accuracy of the segmentation of the artificial intelligence4 monthsThe accuracy of the segmentation of the common bile duct, duodenoscopy and stenosis lesions by the artificial intelligence

Countries

China

Contacts

Primary ContactYanqing Li, MD, PhD
liyanqing@sdu.edu.cn053182169385
Backup ContactRui Ji, MD, PhD
qljirui@email.sdu.edu.cn18560086103

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026