Artificial intelligence and deep learning: New tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Yoshihisa Takahashi; Erdenetsogt Dungubat; Hiroyuki Kusano; Toshio Fukusato

doi:10.1016/j.csbj.2023.03.048

Artificial intelligence and deep learning: New tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Comput Struct Biotechnol J. 2023 Mar 30:21:2495-2501. doi: 10.1016/j.csbj.2023.03.048. eCollection 2023.

Authors

Yoshihisa Takahashi¹, Erdenetsogt Dungubat^{1

2}, Hiroyuki Kusano¹, Toshio Fukusato³

Affiliations

¹ Department of Pathology, School of Medicine, International University of Health and Welfare, 4-3 Kozunomori, Narita, Chiba 286-8686, Japan.
² Department of Pathology, School of Biomedicine, Mongolian National University of Medical Sciences, Jamyan St 3, Ulaanbaatar 14210, Mongolia.
³ General Medical Education and Research Center, Teikyo University, 2-11-1 Kaga, Itabashi-ku, Tokyo 173-8605, Japan.

Abstract

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated with metabolic syndrome and is rapidly increasing globally with the increased prevalence of obesity. Although noninvasive diagnosis of NAFLD/NASH has progressed, pathological evaluation of liver biopsy specimens remains the gold standard for diagnosing NAFLD/NASH. However, the pathological diagnosis of NAFLD/NASH relies on the subjective judgment of the pathologist, resulting in non-negligible interobserver variations. Artificial intelligence (AI) is an emerging tool in pathology to assist diagnoses with high objectivity and accuracy. An increasing number of studies have reported the usefulness of AI in the pathological diagnosis of NAFLD/NASH, and our group has already used it in animal experiments. In this minireview, we first outline the histopathological characteristics of NAFLD/NASH and the basics of AI. Subsequently, we introduce previous research on AI-based pathological diagnosis of NAFLD/NASH.

Keywords: Artificial intelligence; Machine learning; Nonalcoholic fatty liver disease; Nonalcoholic steatohepatitis; Pathological diagnosis.

Publication types

Review