Artificial intelligence and image guidance in minimally invasive pancreatic surgery: current status and future challenges

Abstract

Artificial intelligence (AI), machine learning (ML), and image guidance are increasingly being used to support surgeons in preoperative, intraoperative, and postoperative decision making and optimized patient care. Surgery is the cornerstone of curative treatment in pancreatic diseases, and a large amount of perioperative data are becoming available with the widespread application of minimally invasive surgical techniques. AI is showing promise in the prediction of malignancy and resectability from preoperative images. A further clinical focus is the prediction of postoperative complications, especially pancreatic fistula, and several AI algorithms now outperform conventional fistula risk scores. Future research will be directed toward refinement of intraoperative decision support systems, individualization of surgical training, and improvement of pre- and postoperative oncologic risk stratification to personalize the sequence of surgery and chemotherapy. This review summarizes recent developments in AI and image guidance for pancreatic surgery.

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