Publication Name	World Journal of Gastroenterology
Manuscript ID	108807
Country	Japan

Category	Gastroenterology & Hepatology
Manuscript Type	Observational Study
Article Title	Image analysis of cardiac hepatopathy secondary to heart failure: Machine learning vs gastroenterologists and radiologists
Manuscript Source	Invited Manuscript
All Author List	Suguru Miida, Hiroteru Kamimura, Shinya Fujiki, Taichi Kobayashi, Saori Endo, Hiroki Maruyama, Tomoaki Yoshida, Yusuke Watanabe, Naruhiro Kimura, Hiroyuki Abe, Akira Sakamaki, Takeshi Yokoo, Masanori Tsukada, Fujito Numano, Takeshi Kashimiura, Takayuki Inomata, Yuma Fuzawa, Tetsuhiro Hirata, Yosuke Horii, Hiroyuki Ishikawa, Hirofumi Nonaka, Kenya Kamimura and Shuji Terai
Funding Agency and Grant Number	Funding Agency Grant Number Grant-in-Aid for Research on Hepatitis from the Japan Agency for Medical Research and Development 24fk0210128h0002 Grant-in-Aid for Scientific Research KAKENHI-23K07372
Corresponding Author	Hiroteru Kamimura, MD, PhD, Division of Gastroenterology and Hepatology, Graduate School of Medical and Dental Sciences, Niigata University, 1-757 Asahimachi Dori, Niigata 951-8520, Japan. hiroteruk@med.niigata-u.ac.jp
Key Words	Machine learning; Liver congestion; Heart failure; Artificial intelligence; Image analysis
Core Tip	Using ResNet-based deep learning on paraumbilical vein-level computed tomography images from 179 patients with chronic heart failure, we developed a model to predict tricuspid regurgitation severity. The model outperformed six gastroenterologists and three radiologists, excelling particularly in identifying severe TR. This novel, non invasive approach captures subtle hepatic congestion features, enabling earlier detection of liver dysfunction secondary to heart failure. Our findings highlight the potential of machine learning to enhance diagnostic accuracy and guide timely intervention in congestive hepatopathy management.
Citation	Miida S, Kamimura H, Fujiki S, Kobayashi T, Endo S, Maruyama H, Yoshida T, Watanabe Y, Kimura N, Abe H, Sakamaki A, Yokoo T, Tsukada M, Numano F, Kashimura T, Inomata T, Fuzawa Y, Hirata T, Horii Y, Ishikawa H, Nonaka H, Kamimura K, Terai S. Image analysis of cardiac hepatopathy secondary to heart failure: Machine learning vs gastroenterologists and radiologists. World J Gastroenterol 2025; In press

Received	2025-04-24 05:46
Peer-Review Started	2025-04-24 08:14
To Make the First Decision
Return for Revision	2025-06-12 08:01
Revised	2025-06-23 00:29
Second Decision	2025-08-19 02:43
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-08-19 05:54
Articles in Press	2025-08-19 05:54
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Typeset the Manuscript

ISSN	1007-9327 (print) and 2219-2840 (online)
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