Computational fluid dynamics for vascular assessment in hepatobiliopancreatic surgery: a pilot study and future perspectives.

Abstract

Introduction: In major hepatobiliopancreatic surgery, an accurate preoperative planning is essential. Postoperative impaired blood supply due to arterial disease or variants can cause postoperative complications. Computational fluid dynamics has previously been successful in revealing distinct features of haemodynamic disturbances. The purpose of our study is to describe the feasibility of a computational fluid dynamics model to predict hepatic artery flow and its variations following gastroduodenal (GDA) or common hepatic (CHA) artery ligation.

Material and methods: This is a pilot study including 20 patients undergoing robotic pancreaticoduodenectomy at a single centre. Preoperative images and intraoperative vascular flows were used to the computational model. Three scenarios of the hepatic artery were analysed: (1) without any clamps, (2) clamped GDA and (3) clamped CHA. Patients 1 to 15 were used to develop the model, and patients 15 to 20 were used for model validation. Finally, the model was tested in 3 abnormal cases: celiac trunk stenosis (2) and replaced right hepatic artery (1).

Results: The selected methodology proved to be reproducible, with the CFD model demonstrating 100% accuracy in predicting blood flow redistribution after gastroduodenal artery (GDA) clamping and 80% accuracy following common hepatic artery (CHA) clamping. The model accurately simulated reversed GDA flow in cases of celiac trunk stenosis and displayed independent flow distribution in patients with anatomical variations, even without prior specific model training.

Conclusion: The developed computational model accurately predicts flow variations in the proper hepatic artery in case of gastroduodenal artery and common hepatic artery clamping. Further studies are needed to validate this methodology.