Neoplasms

All Conditions

Digestive System Diseases

Rare Diseases

Cholangiocarcinoma

Bile Duct Neoplasms

Adenocarcinoma

Carcinoma

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Biliary Tract Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Bile Duct Diseases

Biliary Tract Diseases

Gastrointestinal Diseases

Bile Duct Cancer

All Drugs and Chemicals

Complement System Proteins

This group is comprised by patients with suggestive malignant biliary lesions assessed by DSOC for biopsy. In this group, the investigators aim to use as a complement tool an AI model for the detection of features suggestive of malignancy to perform the biopsy on the detecting bounding box signal.

A further follow-up of 6 months is necessary for a confirming diagnosis of neoplastic lesions.

This group is comprised by patients with suggestive malignant biliary lesions assessed by DSOC for biopsy without AI guidance. A further follow-up of 6 months is necessary for a confirming diagnosis of neoplastic lesions.

Patients with a presumptive diagnosis of biliary malignancy will undergo DSOC + Artificial intelligence model (AIWorks) guidance for detection of neoplastic lesion during real-time procedure, tissue sampling acquisition, and histopathological analysis.

DSOC with AI biopsy guidance

Patients with lesions suggestive of malignancy will undergo DSOC without AI guidance for sampling.

Based on the observer´s criteria regarding areas suggestive of malignancy, the collected tissue sample will be sent for histopathological studies.

DSOC biopsy without AI guidance

Carlos Robles-Medranda, MD FASGE

Digital single-operator cholangioscopy (DSOC) has emerged as a medical advance with an important role in the evaluation of indeterminate biliary lesions. This technique has demonstrated higher sensitivity in the guidance for tissue acquisition when compared with standard endoscopic retrograde cholangiopancreatography (ERCP). DSOC-guided biopsy is considered technically safe and successful for tissue collection.

Hand in hand with the development of more precise diagnostic techniques, comes the implementation of artificial intelligence (AI) for diagnostic assessment. For the past decade, the role of artificial intelligence (AI) has been increasing at a rapid pace. In the biliary tract, different models have been proposed for the characterization of malignant features. Nevertheless, to date, the discrepancy between the visual impression of the operator and the histological results obtained by cholangioscopy still present, affecting the accuracy the diagnosis.

Based on the above, the investigators aim to assess the diagnostic accuracy of AI for the guidance of tissue acquisition with DSOC compared to DSOC without AI for suspected cholangiocarcinoma. As a secondary aim, the investigators pursue to compare quality of AI-guided biopsies samples vs. DSOC biopsies without AI.

The diagnosis and management of biliary malignancy currently represents a medical challenge. To date, DSOC has demonstrated high sensitivity in the detection of malignant biliary lesions, nevertheless there is not a universal expert consensus for the characterization of this lesions. Also, DSOC has shown to be safe and successful for specimen collection with higher sensitivity when compared with standard ERCP.

Moreover, most of the AI models proposed for characterization of neoplastic features in biliary lesions have demonstrated high reliability during DSOC performance. A model was the proposed by investigators in Ecuador, focused on the identification of features of malignancy. The detection is performed by surrounding the suspected lesion in a bounding box. The detected area is displayed in the right side of the screen. Also, the box/image of the presumptive lesion can also be recorded and reviewed afterwards. After the AI model detects the "malignant area", a tissue sample is collected and taken for histopathological studies.

In addition, due to a variation of the endoscopists´ intra and interobserver agreement and the discrepancy between the visual impression and histopathological findings, the investigators intend to take advantage of our AI model as a diagnostic tool for a more precise acquisition of tissue in lesions suggestive of malignancy during real-time DSOC.

AI Guidance for Biopsy in Suspected Cholangiocarcinoma

Efficacy of Artificial Intelligence Aid-digital Single-operator Cholangioscopy (DSOC) Guided-biopsy Sampling in Suspected Cholangiocarcinoma: A Prospective, Randomized Trial

To confirm the diagnosis based on pathology results from specimens obtained through DSOC (with or without AI-guided biopsy) or findings from further indicated procedures, including brush cytology fluoroscopy-guided biopsy, endoscopic ultrasound-guided tissue sampling, and surgical samples.

Finally, the gold standard is a six-month follow-up compared against the AI model (group 1) or the DSOC endoscopist experts' classification. The data will be verified through a 2 x 2 contingency table.

Four biopsies will be performed per each case. Rate of insufficient samples by each study group will be recorded and compared.

Instituto Ecuatoriano de Enfermedades Digestivas

Principal Investigator

Gland and Hormone Related Diseases

Symptoms and General Pathology

Pancreatic Neoplasms

Adenoma

Cholangitis

Constriction, Pathologic

Cholestasis

Cholangitis, Sclerosing

Adenoma, Bile Duct

Papilloma, Intraductal

Cholestasis, Extrahepatic

Pathological Conditions, Anatomical

Endocrine Gland Neoplasms

Pancreatic Diseases

Endocrine System Diseases

Pancreatic Cancer

Primary Sclerosing Cholangitis

Experienced Endoscopists with significant user experience with Volumetric Laser Endomicroscopy for bile duct/pancreatic duct strictures

Experienced Endoscopists with non-significant or beignner user experience with Volumetric Laser Endomicroscopy for bile duct/pancreatic duct strictures

Interobserver agreement or Interrater agreement using 9 visual criteria for diagnosing VLE clips that feature indeterminate biliary or pancreatic duct strictures

Interobserver agreement or Interrater agreement

Michel Kahaleh, MD

The purpose of this study is to assess the interobserver agreement (IOV) for pancreatico-biliary Volumetric Laser Endomicroscopy (VLE) de-identified clips using the new VLE criteria.

This is an Interobserver study to validate VLE criteria for indeterminate biliary and pancreatic duct strictures and evaluate impact on clinical management.

Objective: Validate diagnostic impact of VLE diagnostic accuracy on clinical management

Primary Objectives:

1. Interobserver study for criteria validation and accuracy, Positive predictive value (PPV) and Negative predictive value (NPV), sensitivity and specificity.
2. Evaluation of VLE diagnostics on clinical management (increased accuracy/faster detection)
3. Determination of learning curve to standardize credentialing for endoscopists to use and interpret VLE imaging for biliary/pancreatic treatment management.

B. Hypotheses / Research Question(s) The new VLE criteria for biliary and pancreatic duct strictures increase accuracy, thus leading to substantial impact on clinical management (Screening and Treatment)

Study Design (2 phase):

* Phase 1: Primary Objective 1 and 2 part of the study will be completed.
* Phase 2: Primary Objective 3 of the study will be conducted within 1 month.

Study Timeline: 3 months post WIRB approval. Sample size: 40 VLE Clips of at least 20 seconds featuring one or more the VLE criteria. All clips will have confirmed diagnosis for accuracy analysis. All clips will be de-identified. All clips will be removed from RedCAP and other secure cloud storage upon completion of study.

Clips will be supplied by NinePoint Medical, the company behind VLE OCT. All VLE clips will be from a dataset of clips collected from adults \> 18 and who underwent Endoscopic retrograde cholangiopancreatography (ERCP) with indeterminate biliary stricture indications. The clips are chosen based on the quality of the clips, duration, final diagnosis and presence of either benign or malignant criteria.

Investigators: Up to 30 Expert and non-expert endoscopists currently using VLE

Volumetric Laser Endomicroscopy's (VLE) Diagnostic Accuracy Validation Study: Impact on Clinical Management Study

Interobserver study for criteria validation and accuracy, PPV and NPV, sensitivity and specificity

Correlation analysis of any of the 9 visual criteria with malignancy diagnosis as determined by endoscopist

Learning curve using CUSUM analysis to standardize credentialing for endoscopists to use and interpret VLE imaging for biliary/pancreatic treatment management proficiently.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
AI Guidance for Biopsy in Suspected Cholangiocarcinoma	NCT05374122	Neoplasms Non-Neoplastic Bile Duct Neopl... Bile Duct Lesio...	DSOC with AI bi... DSOC biopsy wit...	18 Years - 99 Years	Instituto Ecuatoriano de Enfermedades Digestivas
AI Guidance for Biopsy in Suspected Cholangiocarcinoma	NCT05374122	Neoplasms Non-Neoplastic Bile Duct Neopl... Bile Duct Lesio...	DSOC with AI bi... DSOC biopsy wit...	18 Years - 99 Years	Instituto Ecuatoriano de Enfermedades Digestivas
Volumetric Laser Endomicroscopy's (VLE) Diagnostic Accuracy Validation Study: Impact on Clinical Management Study	NCT03951324	Biliary Strictu... Pancreas Cancer Cholangiocarcin... Bile Duct Cance... Bile Duct Neopl... Bile Duct Neopl... Bile Duct Lesio... Bile Duct Obstr... Bile Duct Disea... Bile Duct Obstr... Bile Duct Steno... Bile Duct Adeno... Pancreatic Duct... Pancreatic Duct... Pancreatic Duct... Pancreatic Duct... Primary Scleros...	Interobserver a...	18 Years -	Innovative Digestive Health Education and Research Inc

Spots Global Cancer Trial Database for bile duct lesions