Kusano Y, Funada K, Yamaguchi M, Sugawara M, Tamano M. Dietary counseling based on artificial intelligence for patients with nonalcoholic fatty liver disease. Artif Intell Gastroenterol 2022; 3(4): 105-116 [DOI: 10.35712/aig.v3.i4.105]
Corresponding Author of This Article
Masaya Tamano, PhD, Professor, Department of Gastroenterology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minami-Koshigaya, Koshigaya 343-8555, Saitama, Japan. mstamano@dokkyomed.ac.jp
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Prospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Yumi Kusano, Kei Funada, Mayumi Yamaguchi, Masaya Tamano, Department of Gastroenterology, Dokkyo Medical University Saitama Medical Center, Koshigaya 343-8555, Saitama, Japan
Miwa Sugawara, Nutrition Unit, Dokkyo Medical University Saitama Medical Center, Koshigaya 343-8555, Saitama, Japan
Author contributions: Kusano Y reviewed the literature and contributed to manuscript drafting; Funada K analyzed and interpreted the imaging findings; Yamaguchi M drafted the tables and figures; Sugawara M conducted dietary counseling for patients; Tamano M revised the manuscript for important intellectual content; all authors issued final approval for the version to be submitted.
Institutional review board statement: Approval was obtained from the Biomedical Ethics Committee of the authors’ affiliated hospital (No. 2014).
Clinical trial registration statement: The clinical trial is registered with clinical research support office of the authors' affiliated hospital. Details can be found at https://dept.dokkyomed.ac.jp/dep-k/gast/.
Informed consent statement: Written informed consent was obtained from all patients for publication of this report and any accompanying images.
Conflict-of-interest statement: None of the authors have any commercial or financial involvements in connection with this study that represent or appear to represent any conflicts of interest.
Data sharing statement: Participants gave informed consent for data sharing.
CONSORT 2010 statement: The authors have read the CONSORT Statement—checklist of items, and the manuscript was prepared and revised according to the CONSORT Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Masaya Tamano, PhD, Professor, Department of Gastroenterology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minami-Koshigaya, Koshigaya 343-8555, Saitama, Japan. mstamano@dokkyomed.ac.jp
Received: June 22, 2022 Peer-review started: June 22, 2022 First decision: July 11, 2022 Revised: July 13, 2022 Accepted: October 26, 2022 Article in press: October 26, 2022 Published online: October 28, 2022 Processing time: 128 Days and 0.2 Hours
Abstract
BACKGROUND
About 25% of the general population in Japan are reported to have nonalcoholic fatty liver disease (NAFLD). NAFLD and nonalcoholic steatohepatitis carry a risk of progressing further to hepatocellular carcinoma. The primary treatment for NAFLD is dietary therapy. Dietary counseling plays an essential role in dietary therapy. Although artificial intelligence (AI)-based nutrition management software applications have been developed and put into practical use in recent years, the majority focus on weight loss or muscle strengthening, and no software has been developed for patient use in clinical practice.
AIM
To examine whether effective dietary counseling is possible using AI-based nutrition management software.
METHODS
NAFLD patients who had been assessed using an AI-based nutrition management software application (Calomeal) that automatically analyzed images of meals photographed by patients and agreed to receive dietary counseling were given dietary counseling. Blood biochemistry tests were performed before (baseline) and 6 mo after (6M follow-up) dietary counseling. After the dietary counseling, the patients were asked to complete a questionnaire survey.
RESULTS
A total of 29 patients diagnosed with NAFLD between August 2020 and March 2022 were included. There were significant decreases in liver enzyme and triglyceride levels at the 6M follow-up compared to baseline. The food analysis capability of the AI used by Calomeal in this study was 75.1%. Patient satisfaction with the AI-based dietary counselling was high.
CONCLUSION
AI-based nutrition management appeared to raise awareness of dietary habits among NAFLD patients. However, it did not directly alleviate the burden of registered dietitians, and improvements are much anticipated.
Core Tip: Use of artificial intelligence (AI)-based nutrition management software (Calomeal) appeared to raise awareness of nonalcoholic fatty liver disease patients’ dietary habits, and they showed significant decreases in liver enzyme and triglyceride levels at the 6-mo follow-up compared to baseline. The food analysis capability of the AI package used in this study was 75.1%, and patient satisfaction with the AI-based dietary counselling was high. However, due to the limitations of the food analysis capabilities of AI, it did not directly alleviate the burden of registered dietitians, and improvements in the analytical capabilities of AI are much anticipated.
