Current status and future perspective of artificial intelligence analysis for the diagnosis of pancreatobiliary diseases using endoscopic ultrasonography images

Abstract

Pancreatic diseases are challenging to diagnose definitively with only CT or MRI, and procedures such as endoscopic ultrasonography (EUS) and EUS-guided fine needle aspiration (EUS-FNA) are necessary. However, these procedures are highly operator-dependent, making it challenging to standardize their quality. Artificial intelligence (AI) has started to be utilized in medical image diagnosis and is becoming integrated into clinical practice. While no AI models specifically for pancreatic diseases are approved in Japan, there have been several research reports on AI for detecting and differentiating pancreatic tumors and cysts. Since pancreatic disease prevalence is lower than gastrointestinal diseases, the cost of collecting the data necessary for AI development is higher, which has delayed progress in this field. It is necessary to establish efficient data collection methods and learning strategies to promote AI development for diagnosing not only pancreatic diseases but also other low-prevalence conditions.