Artificial intelligence for surgical safety during laparoscopic gastrectomy for gastric cancer: Indication of anatomical landmarks related to postoperative pancreatic fistula using deep learning.

Journal: Surgical endoscopy
PMID: 39093411

Abstract

BACKGROUND: Postoperative pancreatic fistula (POPF) is a critical complication of laparoscopic gastrectomy (LG). However, there are no widely recognized anatomical landmarks to prevent POPF during LG. This study aimed to identify anatomical landmarks related to POPF occurrence during LG for gastric cancer and to develop an artificial intelligence (AI) navigation system for indicating these landmarks.

Authors

  • Yoshimasa Aoyama
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Yusuke Matsunobu
    Faculty of Information Engineering, Department of Information and Systems Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka-City, Fukuoka, 811-0295, Japan.
  • Tsuyoshi Etoh
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Kosuke Suzuki
    Department of Engineering, Nagoya Institute of Technology, Aichi, Japan.
  • Shunsuke Fujita
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Takayuki Aiba
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Hajime Fujishima
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Shinichiro Empuku
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Yohei Kono
    Department of Advanced Medical Research and Development for Cancer and Hair [Aderans], Faculty of Medicine, Oita University, Oita, Japan.
  • Yuichi Endo
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Yoshitake Ueda
    Department of Comprehensive Surgery for Community Medicine, Faculty of Medicine, Oita University, Oita, Japan.
  • Hidefumi Shiroshita
    Department of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita, Japan.
  • Toshiya Kamiyama
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Takemasa Sugita
    Advanced AI Technology Research, Advanced Software Technology Research, Olympus Corporation, Tokyo, Japan.
  • Kenichi Morishima
    Advanced AI Technology Research, Advanced Software Technology Research, Olympus Corporation, Tokyo, Japan.
  • Kohei Ebe
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Tatsushi Tokuyasu
    Faculty of Information Engineering, Department of Information and Systems Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka-City, Fukuoka, 811-0295, Japan. tokuyasu@fit.ac.jp.
  • Masafumi Inomata
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.

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