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Background <p>We have developed gastric cancer/gastrectomy artificial intelligence (gAI) that leverages the tacit knowledge of experienced surgeons to visualize anatomical landmarks, including the pancreas and dimpling lines (DLs), to help prevent pancreatic fistula in laparoscopic gastrectomy for gastric cancer. However, whether gAI contributes to the awareness among surgeons remains unclear. Therefore, in the present study, we aimed to evaluate how gAI intervention influences anatomical landmark recognition, which reflects the awareness of these landmarks among surgeons, and how its effects vary by surgical expertise.</p> Methods <p>An external evaluation committee established the consensus reference standard and validated gAI. Twelve surgeons from four institutions were grouped by expertise as follows: junior trainee, senior trainee, and trainer. Each surgeon viewed videos of the infrapyloric and suprapancreatic areas without and with gAI, annotating images from each scene. Subjective recognition change rate and recognition score difference in anatomical landmark recognition compared to reference standards were assessed across expertise levels.</p> Results <p>In the infrapyloric area, subjective recognition change rates were 52% for junior trainees, 38% for senior trainees, and 9% for trainers, with trainers exhibiting significantly lower rates than both trainee groups (<i>p</i> &lt; 0.001 for both). In the suprapancreatic area, the corresponding rates were 38, 17, and 4%, respectively; trainers exhibited significantly lower rates than junior trainees (<i>p</i> &lt; 0.001) but not senior trainees (<i>p</i> = 0.054). In exploratory analyses limited to observations with measured score changes, recognition scores for the DL between the mesogastrium and pancreas increased significantly in junior trainees in the suprapancreatic area (<i>p</i> &lt; 0.01) and senior trainees in the infrapyloric area (<i>p</i> = 0.03).</p> Conclusions <p>This exploratory study suggests that gAI intervention could support awareness of anatomical landmark recognition in laparoscopic gastrectomy with differential effects across expertise levels, particularly among novice surgeons.</p> Graphical abstract <p></p>

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Impact of artificial intelligence intervention on awareness of anatomical landmarks in laparoscopic gastrectomy: An exploratory study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月1日

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  • Takumi Hasegawa,
  • Tsuyoshi Etoh,
  • Tomoki Nakano,
  • Yoshimasa Aoyama,
  • Yusuke Matsunobu,
  • Reo Fujishima,
  • Shunsuke Fujita,
  • Yuki Shitomi,
  • Tomonori Akagi,
  • Shigeo Ninomiya,
  • Yoshitake Ueda,
  • Tatsushi Tokuyasu,
  • Masafumi Inomata

摘要

Background

We have developed gastric cancer/gastrectomy artificial intelligence (gAI) that leverages the tacit knowledge of experienced surgeons to visualize anatomical landmarks, including the pancreas and dimpling lines (DLs), to help prevent pancreatic fistula in laparoscopic gastrectomy for gastric cancer. However, whether gAI contributes to the awareness among surgeons remains unclear. Therefore, in the present study, we aimed to evaluate how gAI intervention influences anatomical landmark recognition, which reflects the awareness of these landmarks among surgeons, and how its effects vary by surgical expertise.

Methods

An external evaluation committee established the consensus reference standard and validated gAI. Twelve surgeons from four institutions were grouped by expertise as follows: junior trainee, senior trainee, and trainer. Each surgeon viewed videos of the infrapyloric and suprapancreatic areas without and with gAI, annotating images from each scene. Subjective recognition change rate and recognition score difference in anatomical landmark recognition compared to reference standards were assessed across expertise levels.

Results

In the infrapyloric area, subjective recognition change rates were 52% for junior trainees, 38% for senior trainees, and 9% for trainers, with trainers exhibiting significantly lower rates than both trainee groups (p < 0.001 for both). In the suprapancreatic area, the corresponding rates were 38, 17, and 4%, respectively; trainers exhibited significantly lower rates than junior trainees (p < 0.001) but not senior trainees (p = 0.054). In exploratory analyses limited to observations with measured score changes, recognition scores for the DL between the mesogastrium and pancreas increased significantly in junior trainees in the suprapancreatic area (p < 0.01) and senior trainees in the infrapyloric area (p = 0.03).

Conclusions

This exploratory study suggests that gAI intervention could support awareness of anatomical landmark recognition in laparoscopic gastrectomy with differential effects across expertise levels, particularly among novice surgeons.

Graphical abstract