Application Feasibility of Virtual Models and Computational Fluid Dynamics for the Planning and Evaluation of Aortic Repair Surgery for Williams Syndrome

Accurate diagnosis and evaluation of Williams Syndrome (WS) is crucial but difficult for the surgical management and long-term prognosis of patients. Computational fluid dynamics (CFD) based on virtual surgery can visualize surgical planning and predict postoperative haemodynamics, which helps researchers and surgeons better assess the impact of vascular structure on blood flow patterns. In this study, we conducted a haemodynamic evaluation of cardiovascular disease in WS and used virtual surgery and CFD for surgical guidance and postoperative evaluation. A patient diagnosed with WS was included in the study, and a 3D model and haemodynamic analysis were used to guide and evaluate the operation. Compared with traditional methods, virtual models and CFD make diagnoses from invisible to visible, from nonintuitive to intuitive, and from qualitative to quantitative. In the analysis of haemodynamics, CFD results of predictive surgical models and that of the postoperative surgical models reflect a high degree of consistency. There was a small difference in the circumference between the prediction model and the postoperative model (mean ± SD: 1.17 ± 0.23 mm). The haemodynamics of the aorta significantly improved after the operation. The velocity at the sinotubular junction decreased from 3 m/s before the operation to 1 m/s in the virtual model and 1.1 m/s in the postoperative model, while the maximum time average wall shear stress decreased from 158 Pa before the operation to 25 Pa in the postoperative model. Surgical repair increased the proportion of outlet flow of dAo from 28.7–35.5%. The method of predicting aortic repair surgery for WS through virtual surgery and CFD has been suggested to be accurate and feasible.