Artificial intelligence development in pathological diagnosis of pancreatic EUS-FNAB

Abstract

Most histological types of malignant pancreatic tumors are adenocarcinomas. Therefore, understanding the characteristics of these adenocarcinomas is crucial. However, tissue specimens obtained using endoscopic ultrasound-guided fine-needle biopsy (EUS-FNAB) tend to be small and prone to mechanical damage, thereby presenting challenges in terms of diagnostic accuracy. Furthermore, since EUS-FNAB is performed through a transgastric or transduodenal approach, contamination complicates the histological diagnosis. In recent years, the development of artificial intelligence (AI), which is being implemented in clinical settings, has advanced the field of pathology. AI applications are being explored for pancreatic pathological diagnosis. In this article, we summarize the diagnostic system developed by our research group and discuss the recent advancements in AI applications for pathological diagnosis.