A Convolutional Neural Network for Difficult Biliary Cannulation

The main purpose of the study is to train a convolutional neural network (CNN) to predict difficult biliary canulation (DBC) following the European Society of Gastrointestinal Endoscopy Society (ESGE). Consecutive patients undergoing an endoscopic retrograde cholangiopancreatography (ERCP) will be included in the study. Several pictures of the second portion of the duodenum including the ampulla will be taken, along with several pictures of the radiological image. Pictures prospectively collected from the study PRECABIDO (NCT06591364), a multicenter study whith the purpose of evaluating the prevalence of difficult biliary cannulation and predictive factors for difficult cannulation and cannulation failure using ESGE criteria were also used for the training of the CNN.

We will also assess:

A validation of the CNN assessing the agreement between ESGE criteria and the CNN prediction.

To design a novel application based on the use of a convolutional neural network (CNN) to detect difficult biliary cannulation.

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