Background: Recently, computational fluid dynamics (CFD) has been used to simulate blood flow of symptomatic intracranial atherosclerotic stenosis (sICAS) and investigate the clinical implications of its haemodynamic features, which were systematically reviewed in this study.
Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology statements, we searched PubMed and Embase up to March 2024 and screened for articles reporting clinical implications of haemodynamic parameters in sICAS derived from CFD models.
Results: 19 articles met the inclusion criteria, all studies recruiting patients from China. Most studies used CT angiography (CTA) as the source image for vessel segmentation, and generic boundary conditions, rigid vessel wall and Newtonian fluid assumptions for CFD modelling, in patients with 50%-99% sICAS. Pressure and wall shear stress (WSS) were quantified in almost all studies, and the translesional changes in pressure and WSS were usually quantified with a poststenotic to prestenotic pressure ratio (PR) and stenotic-throat to prestenotic WSS ratio (WSSR). Lower PR was associated with more severe stenosis, better leptomeningeal collaterals, prolonged perfusion time and internal borderzone infarcts. Higher WSSR and other WSS measures were associated with positive vessel wall remodelling, regression of luminal stenosis and artery-to-artery embolism. Lower PR and higher WSSR were both associated with the presence and severity of cerebral small vessel disease. Moreover, translesional PR and WSSR were promising predictors for stroke recurrence in medically treated patients with sICAS and outcomes after acute reperfusion therapy, which also provided indicators to assess the effects of stenting treatment on focal haemodynamics.
Conclusions: CFD is a promising tool in investigating the pathophysiology of ICAS and in risk stratification of patients with sICAS. Future studies are warranted for standardisation of the modelling methods and validation of the simulation results in sICAS, for its wider applications in clinical research and practice.
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