Artificial Intelligence in EUS for Diagnosing Pancreatic Solid Lesions

Pancreatic Ductal Adenocarcinoma Clinical Trial

Official title: Utilization of Artificial Intelligence for the Development of an EUS-convolution Neural Network Model Trained to Differentiate Pancreatic Cancer From Other Pancreatic Solid Lesions

Status Completed

Clinical Trial Summary

We aim to develop an EUS-AI model which can facilitate clinical diagnosis by analyzing EUS pictures and clinical parameters of patients.

Clinical Trial Description

EUS is considered to be a more sensitive modality than CT in detecting pancreatic solid lesions due to its high spatial resolution. However, the diagnostic performance is largely dependent on the experience and the technical abilities of the practitioners. Therefore, we aim to develop an objective EUS diagnostic model based on the convolutional neural network, an artificial intelligence technique. In addition, clinical parameters such as risk factors, tumor biomarkers and radiology findings are also added to this artificial intelligence model in order to mimic the actual clinical diagnosis procedures and to increase the performance of this model. ;

Related Conditions & MeSH terms

• Autoimmune Pancreatitis
• Neuroendocrine Tumors
• Pancreatic Ductal Adenocarcinoma
• Pancreatic Neuroendocrine Tumor
• Pancreatitis
• Pancreatitis, Chronic

• NCT number: NCT05476978
• Study type: Observational
• Source: Huazhong University of Science and Technology
• Status: Completed
• Start date: July 1, 2022
• Completion date: January 24, 2024