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Research ArticleClinical Studies

Development of a Novel Artificial Intelligence System for Laparoscopic Hepatectomy

KODAI TOMIOKA, TAKESHI AOKI, NAO KOBAYASHI, YOSHIHIKO TASHIRO, YUTA KUMAZU, HIDEKI SHIBATA, TAKAHITO HIRAI, TATSUYA YAMAZAKI, KAZUHIKO SAITO, KIMIYASU YAMAZAKI, MAKOTO WATANABE, KAZUHIRO MATSUDA, TOMOKAZU KUSANO, AKIRA FUJIMORI and YUTA ENAMI
Anticancer Research November 2023, 43 (11) 5235-5243; DOI: https://doi.org/10.21873/anticanres.16725
KODAI TOMIOKA
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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TAKESHI AOKI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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  • For correspondence: takejp@med.showa-u.ac.jp
NAO KOBAYASHI
2Anaut Inc., Tokyo, Japan
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YOSHIHIKO TASHIRO
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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YUTA KUMAZU
2Anaut Inc., Tokyo, Japan
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HIDEKI SHIBATA
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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TAKAHITO HIRAI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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TATSUYA YAMAZAKI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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KAZUHIKO SAITO
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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KIMIYASU YAMAZAKI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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MAKOTO WATANABE
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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KAZUHIRO MATSUDA
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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TOMOKAZU KUSANO
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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AKIRA FUJIMORI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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YUTA ENAMI
1Division of Gastroenterological and General Surgery, Department of Surgery, School of Medicine, Showa University, Tokyo, Japan;
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Abstract

Background/Aim: Laparoscopic hepatectomy (LH) requires accurate visualization and appropriate handling of hepatic veins and the Glissonean pedicle that suddenly appear during liver dissection. Failure to recognize these structures can cause injury, resulting in severe bleeding and bile leakage. This study aimed to develop a novel artificial intelligence (AI) system that assists in the visual recognition and color presentation of tubular structures to correct the recognition gap among surgeons. Patients and Methods: Annotations were performed on over 350 video frames capturing LH, after which a deep learning model was developed. The performance of the AI was evaluated quantitatively using intersection over union (IoU) and Dice coefficients, as well as qualitatively using a two-item questionnaire on sensitivity and misrecognition completed by 10 hepatobiliary surgeons. The usefulness of AI in medical education was qualitatively evaluated by 10 medical students and residents. Results: The AI model was able to individually recognize and colorize hepatic veins and the Glissonean pedicle in real time. The IoU and Dice coefficients were 0.42 and 0.53, respectively. Surgeons provided a mean sensitivity score of 4.24±0.89 (from 1 to 5; Excellent) and a mean misrecognition score of 0.12±0.33 (from 0 to 4; Fail). Medical students and residents assessed the AI to be very useful (mean usefulness score, 1.86±0.35; from 0 to 2; Excellent). Conclusion: The novel AI presented was able to assist surgeons in the intraoperative recognition of microstructures and address the recognition gap among surgeons to ensure a safer and more accurate LH.

Key Words:
  • Artificial intelligence
  • AI
  • laparoscopic hepatectomy
  • Received August 8, 2023.
  • Revision received August 21, 2023.
  • Accepted September 27, 2023.
  • Copyright © 2023 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
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Anticancer Research: 43 (11)
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Development of a Novel Artificial Intelligence System for Laparoscopic Hepatectomy
KODAI TOMIOKA, TAKESHI AOKI, NAO KOBAYASHI, YOSHIHIKO TASHIRO, YUTA KUMAZU, HIDEKI SHIBATA, TAKAHITO HIRAI, TATSUYA YAMAZAKI, KAZUHIKO SAITO, KIMIYASU YAMAZAKI, MAKOTO WATANABE, KAZUHIRO MATSUDA, TOMOKAZU KUSANO, AKIRA FUJIMORI, YUTA ENAMI
Anticancer Research Nov 2023, 43 (11) 5235-5243; DOI: 10.21873/anticanres.16725

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Development of a Novel Artificial Intelligence System for Laparoscopic Hepatectomy
KODAI TOMIOKA, TAKESHI AOKI, NAO KOBAYASHI, YOSHIHIKO TASHIRO, YUTA KUMAZU, HIDEKI SHIBATA, TAKAHITO HIRAI, TATSUYA YAMAZAKI, KAZUHIKO SAITO, KIMIYASU YAMAZAKI, MAKOTO WATANABE, KAZUHIRO MATSUDA, TOMOKAZU KUSANO, AKIRA FUJIMORI, YUTA ENAMI
Anticancer Research Nov 2023, 43 (11) 5235-5243; DOI: 10.21873/anticanres.16725
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Keywords

  • Artificial intelligence
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