In Journal of gastroenterology ; h5-index 54.0
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Nonalcoholic steatohepatitis (NASH) is an advanced form of NAFLD can progress to liver cirrhosis and hepatocellular carcinoma (HCC). Recently, the prognosis of NAFLD/NASH has been reported to be dependent on liver fibrosis degree. Liver biopsy remains the gold standard, but it has several issues that must be addressed, including its invasiveness, cost, and inter-observer diagnosis variability. To solve these issues, a variety of noninvasive tests (NITs) have been in development for the assessment of NAFLD progression, including blood biomarkers and imaging methods, although the use of NITs varies around the world. The aim of the Japan NASH NIT (JANIT) Forum organized in 2020 is to advance the development of various NITs to assess disease severity and/or response to treatment in NAFLD patients from a scientific perspective through multi-stakeholder dialogue with open innovation, including clinicians with expertise in NAFLD/NASH, companies that develop medical devices and biomarkers, and professionals in the pharmaceutical industry. In addition to conventional NITs, artificial intelligence will soon be deployed in many areas of the NAFLD landscape. To discuss the characteristics of each NIT, we conducted a SWOT (strengths, weaknesses, opportunities, and threats) analysis in this study with the 36 JANIT Forum members (16 physicians and 20 company representatives). Based on this SWOT analysis, the JANIT Forum identified currently available NITs able to accurately select NAFLD patients at high risk of NASH for HCC surveillance/therapeutic intervention and evaluate the effectiveness of therapeutic interventions.
Kamada Yoshihiro, Nakamura Takahiro, Isobe Satoko, Hosono Kumiko, Suama Yukiko, Ohtakaki Yukie, Nauchi Arihito, Yasuda Naoto, Mitsuta Soh, Miura Kouichi, Yamamoto Takuma, Hosono Tatsunori, Yoshida Akihiro, Kawanishi Ippei, Fukushima Hideaki, Kinoshita Masao, Umeda Atsushi, Kinoshita Yuichi, Fukami Kana, Miyawaki Toshio, Fujii Hideki, Yoshida Yuichi, Kawanaka Miwa, Hyogo Hideyuki, Morishita Asahiro, Hayashi Hideki, Tobita Hiroshi, Tomita Kengo, Ikegami Tadashi, Takahashi Hirokazu, Yoneda Masato, Jun Dae Won, Sumida Yoshio, Okanoue Takeshi, Nakajima Atsushi
2022-Dec-05
Artificial intelligence, Biomarker, Elastography, NAFLD/NASH, Scoring system
