Artificial Intelligence for Digital Cholangioscopy Neoplasia Diagnosis

CompletedOBSERVATIONAL
Enrollment

170

Participants

Timeline

Start Date

October 1, 2020

Primary Completion Date

November 30, 2021

Study Completion Date

May 1, 2022

Conditions
Common Bile Duct NeoplasmsNon-Neoplastic Bile Duct Disorder
Interventions
DIAGNOSTIC_TEST

AI model classification

AIWorks is an artificial intelligence model for real-time cholangioscopic detection of neoplastic and non-neoplastic bile duct lesions. It allows you to choose using a video file or a USB camera input as the detection source. Once the input source has been selected, the software performs real-time detection by surrounding the area of interest (i.e., the area with malignancy features) inside a bounding box. All detections made are displayed on the right side of the screen and can also be reviewed afterwards.

DIAGNOSTIC_TEST

DSOC endoscopist experts' classification

"Six endoscopists with high DSOC expertise will observe and classify a set of videos among neoplastic or non-neoplastic bile duct lesions following a Bernoulli distribution; blinded to clinical records and should have never attended said patients.~Gastroenterologists from each center, with non-DSOC responsibility, will select DSOC videos and corresponding baseline data. DSOC videos and data will be gathered in one set. Each video represents a full DSOC for a single patient. The patient will be the unit of this study.~The neoplastic bile duct criteria are in accordance with the Robles-Medranda et al and the Mendoza classifications (ie. Irregular mucosa surface, Tortuous and dilated vascularity, Irregular nodulations, Polyps, Ulceration, Honeycomb pattern, etc.). The experts will assess neoplastic bile duct by presence or absence of disaggregated criteria. Likewise, by Boolean logical operators, the statistical software will compute disaggregated answers."

Trial Locations (6)

77030

Baylor Saint Luke's Medical Center, Houston

77098

Houston Methodist Hospital, Houston

08901

Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University, New Brunswick

Unknown

Department of Advanced Interventional Endoscopy, Universitair Ziekenhuis Brussel (UZB)/Vrije Universiteit Brussel (VUB), Brussels

Serviço de Endoscopía Gastrointestinal do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo

090505

Carlos Robles-Medranda, Guayaquil

All Listed Sponsors
collaborator

The Methodist Hospital Research Institute

OTHER

collaborator

University of Sao Paulo

OTHER

collaborator

Vrije Universiteit Brussel

OTHER

collaborator

Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University

OTHER

collaborator

Baylor St. Luke's Medical Center

OTHER

collaborator

Universitair Ziekenhuis Brussel

OTHER

lead

Instituto Ecuatoriano de Enfermedades Digestivas

OTHER

NCT05147389 - Artificial Intelligence for Digital Cholangioscopy Neoplasia Diagnosis | Biotech Hunter | Biotech Hunter