Artificial Intelligence for Digital Cholangioscopy Neoplasia Diagnosis
- Conditions
- Common Bile Duct NeoplasmsNon-Neoplastic Bile Duct Disorder
- Interventions
- Diagnostic Test: AI model classificationDiagnostic Test: DSOC endoscopist experts' classification
- Registration Number
- NCT05147389
- Lead Sponsor
- Instituto Ecuatoriano de Enfermedades Digestivas
- Brief Summary
Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. To date, there is not a universally accepted DSOC classification. Endoscopists' Intra and interobserver agreements vary widely. Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools is almost exclusively for intrahepatic CCA (iCCA). Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions.
In Ecuador, the investigators have recently proposed an AI model to classify bile duct lesions during real-time DSOC, which accurately detected malignancy patterns. This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with high DSOC experienced endoscopists.
- Detailed Description
Distinguishing neoplastic from non-neoplastic bile duct lesions is a challenge for clinicians. Magnetic resonance (MR) and biopsy guided by endoscopic retrograde cholangiopancreatography (ERCP) reached a negative predictive value (NPV) around 50%. On the other hand, Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. DSOC could be even better than DSOC-guided biopsy, which is inconclusive in some cases. However, to date, there is no universally accepted DSOC classification for that purpose. Also, endoscopists' Intra and interobserver agreements vary widely. Therefore, a more reproducible system is still needed.
With interesting results, Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools has been developed based on imaging radiomics. Nevertheless, CCA AI resources are almost exclusively for intrahepatic CCA (iCCA), with an endoscopic technique. Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions. Perihilar (pCCA) and distal (dCCA) cholangiocarcinoma as the most typical neoplastic bile duct lesions. Both represent 50-60% and 20-30% of all CCA, including secondary malignancies by local extension (hepatocarcinoma, gallbladder, and pancreas cancer).
A recent Portuguese proof-of-concept study developed an AI tool based on convolutional neuronal networks (CNNs). It let to differentiate between malignant from benign bile duct lesions or normal tissue with very high accuracy. Still, it needs more external validation, including endoscopists' Intra and interobserver agreement comparison. In Ecuador, the investigators recently proposed an AI model to classify bile duct lesions during real-time DSOC, which has been able to detect malignancy pattern in all cases.
This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with six endoscopists with high DSOC experience.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 170
- Patients referred to our center with an indication of DSOC due to suspicion of CBD tumor or indeterminate CBD stenosis.
- Patients who authorized for recording DSOC procedure for this study.
- Any clinical condition which makes DSOC inviable.
- Patients with more than one DSOC.
- Low quality of recorded DSOC videos, even for AI model as for the expert endoscopists.
- Lost on a one-year follow-up after DSOC.
- Disagreement between DSOC findings vs. one-year follow-up, even after re-assessment of respective DSOC videos.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Non-neoplastic bile duct lesions AI model classification This group is confirmed by DSOC videos from patients with DSOC-confirmed non-neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The non-neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm non-neoplastic bile duct lesion and the type, when available: acute or chronic cholangitis secondary to stones or parasite's location, autoimmune cholestatic liver diseases as autoimmune sclerosant cholangitis, and primary biliary cholangitis. Based on follow-up, videos from patients with confirmed neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. Neoplastic bile duct lesions DSOC endoscopist experts' classification This group is confirmed by DSOC videos from patients with DSOC-confirmed neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm neoplastic bile duct lesion and the type: pCCA or dCCA, local extension of iCCA, hepatocarcinoma mixed CCA/hepatocarcinoma, gallbladder cancer, pancreas cancer, or any other neoplastic bile duct lesion. Based on follow-up, videos from patients with confirmed non-neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. Neoplastic bile duct lesions AI model classification This group is confirmed by DSOC videos from patients with DSOC-confirmed neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm neoplastic bile duct lesion and the type: pCCA or dCCA, local extension of iCCA, hepatocarcinoma mixed CCA/hepatocarcinoma, gallbladder cancer, pancreas cancer, or any other neoplastic bile duct lesion. Based on follow-up, videos from patients with confirmed non-neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. Non-neoplastic bile duct lesions DSOC endoscopist experts' classification This group is confirmed by DSOC videos from patients with DSOC-confirmed non-neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The non-neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm non-neoplastic bile duct lesion and the type, when available: acute or chronic cholangitis secondary to stones or parasite's location, autoimmune cholestatic liver diseases as autoimmune sclerosant cholangitis, and primary biliary cholangitis. Based on follow-up, videos from patients with confirmed neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification.
- Primary Outcome Measures
Name Time Method Neoplastic bile duct diagnosis confirmation after one year follow-up One year Cases will be first followed up during one year to confirm or discard neoplastic bile duct lesions. A definite diagnosis of neoplastic bile duct lesion will be based on DSOC-guided biopsy specimen or findings from further indicated procedures, including brush cytology fluoroscopy-guided, endoscopic ultrasound-guided tissue sampling, surgical samples, and even imaging test in the context of a more impaired patient. Finally, the agreement between one-year follow-up (gold standard) vs. AI model and DSOC endoscopist experts' classification will be verified through a 2 x 2 contingency table.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (6)
Baylor Saint Luke's Medical Center
🇺🇸Houston, Texas, United States
Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University
🇺🇸New Brunswick, New Jersey, United States
Houston Methodist Hospital
🇺🇸Houston, Texas, United States
Department of Advanced Interventional Endoscopy, Universitair Ziekenhuis Brussel (UZB)/Vrije Universiteit Brussel (VUB)
🇧🇪Brussels, Belgium
Carlos Robles-Medranda
🇪🇨Guayaquil, Guayas, Ecuador
Serviço de EndoscopÃa Gastrointestinal do Hospital das ClÃnicas da Faculdade de Medicina da Universidade de São Paulo
🇧🇷São Paulo, Brazil