Computational Fluid Dynamics-Based Blood Flow Assessment Facilitates Optimal Management of Portal Vein Stenosis After Liver Transplantation

Abstract

BackgroundPortal vein stenosis develops in 3.4–14% of split liver transplantation1–3 and its early detection and treatment are essential to achieve long-term graft survival,2–5 although the diagnostic capability of conventional modalities such as Doppler ultrasound and computed tomography is limited.1,4,5 MethodsThis study used computational fluid dynamics to analyze portal vein hemodynamics in the management of post-transplant portal vein stenosis. To perform computational fluid dynamics analyses, three-dimensional portal vein model was created using computed tomographic DICOM data. The inlet flow condition was set according the flow velocity measured on Doppler ultrasonography. Finally, portal vein flow was simulated on a fluid analysis software (Software Cradle, Japan). ResultsAn 18-month-old girl underwent liver transplantation using a left lateral graft for biliary atresia. At the post-transplant 1-week evaluation, the computational fluid dynamics streamline analysis visualized vortices and an accelerated flow with a velocity ratio < 2 around the anastomotic site. The wall shear stress analysis revealed a high wall shear stress area within the post-anastomotic portal vein. At the post-transplant 6-month evaluation, the streamline analysis illustrated the increased vortices and worsening flow acceleration to reach the proposed diagnostic criteria (velocity ratio > 3:1).3,5 The pressure analysis revealed a positive pressure gradient of 3.8 mmHg across the stenotic site. Based on the findings, the patient underwent percutaneous transhepatic portal venoplasty with balloon dilation. The post-treatment analyses confirmed the improvement of a jet flow, vortices, a high wall shear stress, and a pressure gradient. DiscussionThe computational fluid dynamics analyses are useful for prediction, early detection, and follow-up of post-transplant portal vein stenosis and would be a promising technology in post-transplant management.