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AI Guidance for Biopsy in Suspected Cholangiocarcinoma

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ClinicalTrials.gov Identifier: NCT05374122
Recruitment Status : Active, not recruiting
First Posted : May 16, 2022
Last Update Posted : March 6, 2023
Information provided by (Responsible Party):
Carlos Robles-Medranda, Instituto Ecuatoriano de Enfermedades Digestivas

Brief Summary:

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.

Condition or disease Intervention/treatment Phase
Neoplasms Non-Neoplastic Bile Duct Neoplasms Bile Duct Lesions Diagnostic Test: DSOC with AI biopsy guidance Diagnostic Test: DSOC biopsy without AI guidance Not Applicable

Detailed Description:

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.

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 48 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description: Randomized controlled trial
Masking: None (Open Label)
Primary Purpose: Diagnostic
Official Title: Efficacy of Artificial Intelligence Aid-digital Single-operator Cholangioscopy (DSOC) Guided-biopsy Sampling in Suspected Cholangiocarcinoma: A Prospective, Randomized Trial
Actual Study Start Date : May 1, 2022
Estimated Primary Completion Date : December 30, 2023
Estimated Study Completion Date : May 1, 2024

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Biopsy

Arm Intervention/treatment
Experimental: DSOC + AI-biopsy guidance

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.

Diagnostic Test: DSOC with AI biopsy guidance
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.

Active Comparator: DSOC biopsy without AI guidance
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.
Diagnostic Test: DSOC biopsy without AI 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.

Primary Outcome Measures :
  1. Cholangiocarcinoma diagnosis confirmation after biopsy and six-month follow-up [ Time Frame: Six months ]

    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.

Secondary Outcome Measures :
  1. Insufficient biopsy sample rate [ Time Frame: Six months ]
    Four biopsies will be performed per each case. Rate of insufficient samples by each study group will be recorded and compared.

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 99 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  • Patients referred to our center with an indication of DSOC due to suspicion of CBD tumor or indeterminate CBD stenosis.
  • Patients who authorized for DSOC-guided biopsy.

Exclusion Criteria:

  • Any clinical condition which makes DSOC inviable.
  • Patients with more than one DSOC.
  • Lost on a six-month follow-up after DSOC.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05374122

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Carlos Robles-Medranda
Guayaquil, Guayas, Ecuador, 090505
Sponsors and Collaborators
Instituto Ecuatoriano de Enfermedades Digestivas
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Principal Investigator: Carlos Robles-Medranda, MD FASGE Ecuadorian Institute of Digestive Diseases
Publications of Results:

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Responsible Party: Carlos Robles-Medranda, Principal Investigator, Instituto Ecuatoriano de Enfermedades Digestivas
ClinicalTrials.gov Identifier: NCT05374122    
Other Study ID Numbers: IECED-05052022
First Posted: May 16, 2022    Key Record Dates
Last Update Posted: March 6, 2023
Last Verified: March 2023
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Carlos Robles-Medranda, Instituto Ecuatoriano de Enfermedades Digestivas:
Artificial Intelligence
Additional relevant MeSH terms:
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Bile Duct Neoplasms
Neoplasms, Glandular and Epithelial
Neoplasms by Histologic Type
Biliary Tract Neoplasms
Digestive System Neoplasms
Neoplasms by Site
Bile Duct Diseases
Biliary Tract Diseases
Digestive System Diseases