Application of Artificial Intelligence Based on Preoperative and Intraoperative Imaging to Hepatobiliary Surgery

In recent developments, artificial intelligence (AI) has revolutionized hepatobiliary surgery with applications in simulation, navigation, and outcome prediction. AI contributes to precise preoperative planning by calculating hepatic segmental volumes, extracting detailed vascular and liver data. An artificial neural network predicts postoperative liver failure and early recurrence after hepatic resection for hepatocellular carcinoma. In indocyanine green fluorescence imaging, AI enhances visualization of bile duct anatomy and hepatic tumors. For laparoscopic cholecystectomy, a deep learning-based AI system identifies anatomical landmarks and assesses the “critical view of safety.” The clinical application of AI in hepatobiliary surgery, from preoperative simulation to intraoperative navigation, holds potential to enhance safety and efficacy following thorough validation.