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

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.