AI Guidance for Biopsy in Suspected Cholangiocarcinoma

Neoplasms Clinical Trial

Official title:

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

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT05374122
• Other study ID #: IECED-05052022
• Status: Active, not recruiting
• Phase: N/A
• Start date: May 1, 2022
• Est. completion date: May 1, 2024

Study information

• Verified date: March 2023
• Source: Instituto Ecuatoriano de Enfermedades Digestivas
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 48
• Est. completion date: May 1, 2024
• Est. primary completion date: December 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 99 Years

Eligibility

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.

Related Conditions & MeSH terms

• Bile Duct Lesions
• Bile Duct Neoplasms
• Cholangiocarcinoma
• Neoplasms

Intervention

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.
• 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.

Locations

Country	Name	City	State
Ecuador	Carlos Robles-Medranda	Guayaquil	Guayas

Sponsors (1)

Lead Sponsor	Collaborator
Instituto Ecuatoriano de Enfermedades Digestivas

Country where clinical trial is conducted

Ecuador, 

References & Publications (6)

Ahmed Z, Mohamed K, Zeeshan S, Dong X. Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database (Oxford). 2020 Jan 1;2020:baaa010. doi: 10.1093/database/baaa010. — View Citation

Gerges C, Beyna T, Tang RSY, Bahin F, Lau JYW, van Geenen E, Neuhaus H, Nageshwar Reddy D, Ramchandani M. Digital single-operator peroral cholangioscopy-guided biopsy sampling versus ERCP-guided brushing for indeterminate biliary strictures: a prospective — View Citation

Ribeiro T, Saraiva MM, Afonso J, Ferreira JPS, Boas FV, Parente MPL, Jorge RN, Pereira P, Macedo G. Automatic Identification of Papillary Projections in Indeterminate Biliary Strictures Using Digital Single-Operator Cholangioscopy. Clin Transl Gastroenter — View Citation

Robles-Medranda C, Oleas R, Sanchez-Carriel M, Olmos JI, Alcivar-Vasquez J, Puga-Tejada M, Baquerizo-Burgos J, Icaza I, Pitanga-Lukashok H. Vascularity can distinguish neoplastic from non-neoplastic bile duct lesions during digital single-operator cholang — View Citation

Robles-Medranda C, Valero M, Soria-Alcivar M, Puga-Tejada M, Oleas R, Ospina-Arboleda J, Alvarado-Escobar H, Baquerizo-Burgos J, Robles-Jara C, Pitanga-Lukashok H. Reliability and accuracy of a novel classification system using peroral cholangioscopy for — View Citation

Saraiva MM, Ribeiro T, Ferreira JPS, Boas FV, Afonso J, Santos AL, Parente MPL, Jorge RN, Pereira P, Macedo G. Artificial intelligence for automatic diagnosis of biliary stricture malignancy status in single-operator cholangioscopy: a pilot study. Gastroi — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Cholangiocarcinoma diagnosis confirmation after biopsy and six-month follow-up	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.	Six months
Secondary	Insufficient biopsy sample rate	Four biopsies will be performed per each case. Rate of insufficient samples by each study group will be recorded and compared.	Six months