Clinical implications of haemodynamics in symptomatic intracranial atherosclerotic stenosis by computational fluid dynamics modelling: a systematic review ========================================================================================================================================================== * Yu Liu * Shuang Li * Haipeng Liu * Xuan Tian * Yuying Liu * Ziqi Li * Thomas W Leung * Xinyi Leng ## Abstract **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. * Atherosclerosis * Stroke * Computed Tomography Angiography * Plaque #### WHAT IS ALREADY KNOWN ON THIS TOPIC * CFD is an emerging tool to investigate haemodynamic patterns of sICAS and its clinical implications. However, the CFD modelling methodology, haemodynamic parameters and clinical implications investigated varied among previous studies. #### WHAT THIS STUDY ADDS * In a systematic review, we summarized the CFD modelling methodology, haemodynamic parameters of interest and their associations with other imaging markers and clinical indicators, in existing studies using the CFD technique to investigate haemodynamics of sICAS. #### HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY * This review article provides a summary of the clinical implications of haemodynamics in sICAS based on the CFD technique. It advocates standardisation and validation of the modelling methodology and findings, for future research advance in this area. ## Introduction Intracranial atherosclerotic stenosis (ICAS) is a common cause of ischaemic stroke and transient ischaemic attack (TIA), which accounts for 30%–50% of all ischaemic strokes in Asians and 8%–10% in Caucasians.1 2 Despite optimal medical treatment, patients with stroke or TIA due to ICAS, that is, symptomatic ICAS (sICAS), have a considerable risk of recurrent stroke.3 4 ICAS can be diagnosed with a variety of modalities, such as transcranial Doppler (TCD), MR angiography (MRA), CT angiography (CTA) and digital subtraction angiography (DSA).5 While these imaging techniques are useful tools in identifying vessel lumen changes secondary to atherosclerosis, another emerging tool, computational fluid dynamics (CFD), could furnish other valuable characteristics in ICAS. CFD, modelling flow pattern by solving equations of fluid dynamics, has been a useful tool for researching haemodynamics in cardiovascular and cerebrovascular diseases, for example, wall shear stress (WSS), velocity and pressure.6 Recent studies indicated that CFD is also promising in studying haemodynamics and relevant clinical implications in sICAS.7 Yet, the CFD modelling results rely very much on the assumptions on blood, vessel wall and boundary conditions, which have varied among previous studies in sICAS. The haemodynamic parameters and the clinical implications also differed among previous studies. These may have hindered generalisability of the findings and further progress in this area. We therefore performed this systematic review, summarising the modelling methodology, haemodynamic parameters of interest and the associations with other imaging and clinical indicators, in existing studies using the CFD method to analyse haemodynamics of sICAS. We also intended to discuss limitations of existing studies and propose some future research directions, in the hope of advocating more investigations and advances in this area. ## Methods We conducted this study following Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology statements.8 9 We searched PubMed and Embase database with English full-text articles between January 2000 and March 2024. Key searching terms included ‘intracranial arter*’, ‘cerebral arter*’, ‘steno*’, ‘occlus*’ and ‘atherosclero*’, in combination with ‘haemodynamic*’ and ‘computational fluid dynamic*’ (online supplemental tables S1,S2). Reference lists were also manually searched for eligible studies. ### Supplementary data [[svn-2024-003202supp001.pdf]](pending:yes) Study inclusion criteria were (1) cross-sectional or longitudinal study recruiting patients with sICAS, (2) using CFD models to study focal (adjacent to ICAS lesion) or global cerebral haemodynamics and (3) reporting clinical implications of the haemodynamic metrics from CFD models, for example, associations of the haemodynamic metrics with other imaging markers or clinical features/outcomes. Animal/experimental studies, pure technical papers with no imaging or clinical association investigations, studies simply verifying the CFD-based haemodynamic parameters with invasively measured counterparts, case reports/series or studies with sample size <10 cases, and review, letter and comment articles were excluded. Studies involving both patients with sICAS and patients with extracranial atherosclerotic stenosis, without separate data on those with sICAS, were also excluded. Study characteristics, haemodynamic parameters and the main findings on clinical implications were extracted. The risk of bias was assessed. More details over the methods are described in online supplemental methods. ## Results Among the 5226 articles identified through literature search, 40 remained after screening the title and abstract, of which 19 studies met the inclusion criteria (figure 1). ![Figure 1](http://svn.bmj.com/http://svn.smart01.highwire.org/content/svnbmj/10/1/16/F1.medium.gif) [Figure 1](http://svn.bmj.com/content/10/1/16/F1) Figure 1 Flow chart for study screening. CFD, computational fluid dynamics; ICAS, intracranial atherosclerotic stenosis; sICAS, symptomatic intracranial atherosclerotic stenosis. ### Study and patient characteristics Study characteristics were summarised in table 1, and detailed CFD model setup and clinical implications of each study were described in online supplemental table S3). Of the 19 studies included, 5 were published between 2014 and 2019 and 14 published after 2020. All studies were conducted in China. Regarding the sICAS lesion, 13 and 4 studies, respectively, recruited patients with 50%–99% and 70%–99% stenosis. Additionally, two studies focused on 30%–99% and 50%–70% stenosis, respectively. Nine and one studies limited sICAS in the anterior circulation or posterior circulation, respectively, and nine studies involved both circulations. The sample size was >100 in 5 studies. Most of the included studies were observational and retrospective, and 11 of them had a low risk of bias (online supplemental table S4). View this table: [Table 1](http://svn.bmj.com/content/10/1/16/T1) Table 1 Study characteristics of the 19 primary studies included in this systematic review ### CFD modelling methods CFD modelling for ICAS mostly involves the following steps: (1) reconstruction of the arteries of interest from source images of neurovascular exams; (2) generation of a mesh in the vessel lumen, wall and inlet/outlet; (3) setup of boundary conditions on inlet/outlet and blood properties; (4) simulation of blood flow by solving fluid dynamics equations and (5) postprocessing of haemodynamic parameters (online supplemental figure S1). The software used for CFD modelling in the 19 primary studies was listed in online supplemental table S5). ### Supplementary data [[svn-2024-003202supp002.pdf]](pending:yes) Most studies used CTA as the source images for vessel segmentation, others used time-of-flight MRA, three-dimensional rotational angiography and biplane DSA. In the CFD model setup, most studies used generic boundary conditions, rigid with no-slip vessel wall and Newtonian blood assumptions. Five studies used patient-specific inlet or outlet boundary conditions. Among them, two studies used lumped parameter models to simulate microcirculation resistance on the outlet, and Liu *et al* also considered vascular compliance.10 11 Raynald *et al* developed an innovative computational approach, incorporating patient-specific measurements of pressure-wire and CFD simulation, to evaluate microcirculation resistance and blood flow, which was strongly correlated with TCD-based volumetric flow measurements.12 Six studies simulated transient-state blood flow, while other studies conducted steady-state simulations. ### Haemodynamic metrics of interest Regarding the haemodynamic features, most studies quantified pressure and WSS across the sICAS lesion, and other studies also assessed shear strain rate (SSR), velocity and vorticity. 15 studies used various terms to reflect the pressure change across a sICAS lesion, including pressure ratio (PR) and absolute pressure gradient. PR was calculated as poststenotic pressure distal to the lesion divided by prestenotic pressure in the proximally normal artery segment. The pressure gradient was calculated as the absolute value of prestenotic pressure minus poststenotic pressure. Seven studies assessed WSS, such as WSS ratio (WSSR) or relative WSS (rWSS). Most studies used WSSR, calculated as WSS at the stenotic-throat divided by prestenotic WSS, to reflect WSS change across a sICAS lesion. Some other studies measured rWSS at one location on the vessel wall across a sICAS lesion,13 calculated as the ratio of the absolute WSS value at one location and the mean WSS value across the circumference in the proximally normal artery segment. The principles of calculating WSSR and rWSS were similar, both to offset the effects of individual arterial geometry on focal WSS in comparing the WSS values among individuals. Other studies also evaluated SSR, velocity, vorticity and their related parameters. Leng *et al* and Nam *et al* calculated the ratio of SSR at the stenotic-throat and at the prestenotic arterial segment, and similarly the velocity ratio, to reflect the velocity changes across the sICAS lesion.14 15 ### Correlations of the haemodynamic metrics with anatomical characteristics of the sICAS lesions in cross-sectional and longitudinal studies In cross-sectional studies, Nam *et al* observed in-average lower PR, higher SSR ratio and higher velocity ratio in severe (70%–99%) sICAS lesions than moderate (50%–69%) stenosis (all p<0.001).15 However, PR might not be linearly proportional to the stenosis rate in sICAS, according to Liu *et al*.11 In addition, Zhang *et al* found higher WSSR (medians 9.98 vs 5.99, p=0.004) and WSS (means 53.99 Pa vs 39.98 Pa, p=0.023) at the narrowest location in patients with symptomatic middle cerebral artery (MCA) stenosis with positive remodelling than those with negative remodelling in high-resolution MRI (HRMRI), while the remodelling index (Pearson’s r=0.376, p=0.026) and plaque area (Pearson’s r=0.407, p=0.015) were positively correlated with WSSR.16 In a longitudinal study, Lan *et al* associated a higher maximum WSS (adjusted OR (aOR), 1.20; 95 % CI, 1.03 to 1.39; p=0.019) and larger mean rWSS of the high-WSS region (aOR, 1.53; 95% CI, 1.07 to 2.19; p=0.021) with regression of luminal stenosis in sICAS in CTA over 1 year, in medically treated patients; such associations were similar when analysing the proximal and distal segments of the lesion separately.13 It was speculated that positive remodelling may play a role underlying such associations, which, however, could not be verified in this study using CTA only to assess features of the sICAS lesions. These findings indicated complicated relationships between the haemodynamic and anatomical features of sICAS lesions that warrant further investigations. ### Correlations with collateral and perfusion status in cross-sectional studies In cross-sectional studies, CFD models were used to investigate haemodynamic metrics affecting leptomeningeal collateral (LMC) and perfusion status in patients with sICAS. Leng *et al* found the correlation of a larger pressure gradient with better LMCs in patients with sICAS (aOR for 10 mm Hg increment in absolute pressure gradient, 1.70; 95% CI, 1.06 to 2.74; p=0.029), which indicated a significant translesional pressure drop served as a driving force for recruiting LMCs.17 In addition, Lan *et al* investigated the interrelationships among antegrade residual flow through symptomatic MCA stenosis (as reflected by translesional PR in CFD models), LMC flow assessed in CTA that could retrogradely perfuse distal brain territories and the overall cerebral perfusion measured in CT perfusion (CTP).18 The study showed lower PR (means 0.79 vs 0.90, p=0.015) and better LMC status (56.7% vs 34.5% with good LMCs, p=0.079) among patients with severe stenosis (70%–99%) than those with moderate stenosis (50%–69%). Moreover, the study also indicated that cerebral perfusion in the supplying territory of a stenotic MCA may depend more on LMC flow (Pearson’s r=0.038, p=0.051) among patients with severe stenosis but more on antegrade residual flow (Pearson’s r=−0.605, p<0.001) among those with moderate stenosis. In another study, Wang *et al* found a negative correlation between PR and Tmax (Spearman’s r=−0.73, p<0.01), the duration to the maximum of residue function in perfusion-weighted MRI, which means a larger translesional pressure gradient associating with prolonged perfusion time.19 Yin *et al* found a significantly lower PR in patients with sICAS with apparent hypoperfusion than those with normal perfusion defined in 4D CTA (means 0.38 vs 0.76, p<0.01), although the sample size was small for the analysis (n=10).10 In addition, Raynald *et al* observed a good agreement on the blood flow rate derived from CFD modelling and TCD measurements (mean difference: −0.78 mL/s, p for Bland-Altman test=0.027), while the mean velocities showed less agreement between CFD simulation and TCD measurements (mean difference: −0.05 cm/s, p for Bland-Altman test=0.399), which indicated greatly varied flow resistance among individuals.12 Overall, these studies have revealed the role of translesional pressure gradient across sICAS lesions in affecting the distal collateral and perfusion status, while various factors could affect these relationships. Of note, none of these studies reported data separately in patients with posterior-circulation sICAS, for whom standard perfusion parameters have not been established and more investigations are needed. ### Correlations with stroke mechanisms in cross-sectional studies ICAS can cause an ischaemic stroke or TIA via different mechanisms with different infarct topography, for example, hypoperfusion (usually with borderzone infarcts), artery-to-artery embolism (usually with multiple cortical or territorial infarcts) and parent artery atherosclerosis occluding penetrating artery (usually with single subcortical small infarct). The stroke mechanisms have been associated with different risks of stroke relapse in medically treated patients with sICAS.20 The associations between haemodynamic features of sICAS in CFD models and stroke mechanisms have been investigated in studies by Feng *et al* 21 and Li *et al*.22 First, Feng *et al* found high WSSR as an independent predictor of artery-to-artery embolism as a stroke mechanism (aOR, 3.90; 95% CI, 1.22 to 12.47; p=0.022), in patients with sICAS in the anterior circulation.21 More interestingly, such association was more prominent in those with a low PR (large translesional pressure gradient). In addition, Li *et al* compared haemodynamic features of sICAS lesions and other imaging characteristics between patients with sICAS with internal and cortical borderzone infarcts, in whom hypoperfusion has usually been considered as the stroke mechanism.22 They found low PR (PR≤median) independently associated with internal borderzone infarcts (aOR: 4.22, p=0.026) and higher incidence of coexisting small cortical infarcts in those with cortical borderzone infarcts. The findings suggested artery-to-artery embolism as a possible pathogenic mechanism underlying cortical borderzone infarcts, which was against previous speculations. Overall, these studies indicated important roles of haemodynamics in determining the stroke mechanisms in sICAS, while further studies are needed to explain and verify the findings. ### Correlations with cerebral small vessel disease in cross-sectional study Cerebral small vessel disease (CSVD) commonly coexists with ICAS, particularly in older individuals.23 In a cross-sectional study, Zheng *et al* 24 associated abnormal PR (PR≤median) and WSSR (WSSR≥fourth quartile) with moderate-to-severe white matter hyperintensities (aOR: 10.12, p=0.018), presence of cortical microinfarcts (aOR: 5.25, p=0.003) and moderate-to-severe overall CSVD burden (aOR: 12.55, p=0.033) in the ipsilateral hemisphere to sICAS, independent of these CSVD imaging markers and overall burden in the contralateral hemisphere. The study indicated the role of haemodynamics in affecting the severity of CSVD in patients with sICAS. ### Correlations with risk of recurrent stroke in medically treated patients with sICAS In a pilot study, Leng *et al* 14 associated higher SSR ratio (HR, 1.03; 95% CI, 1.00 to 1.05; p=0.023) and higher velocity ratio (HR, 1.03, 95% CI, 1.00 to 1.06; p=0.035) with a higher risk of recurrent ischaemic stroke in the same territory within 1 year, in medically treated patients with sICAS with 70%–99% stenosis. Additionally, a lower PR also tended to be correlated with the stroke risk, however, which did not achieve statistical importance (HR, 0.98; 95% CI, 0.97 to 1.00; p=0.074). This study demonstrated that stenosis rate may not be the sole or primary indicator for assessing the risk of recurrent stroke in patients with sICAS. In the subsequent Stroke Risk and Haemodynamics in Intracranial Atherosclerotic Disease (SOpHIA) study of 245 patients with sICAS with 50%–99% stenosis, low PR (PR≤median, adjusted HR (aHR), 3.16; 95% CI, 1.15 to 8.72; p=0.026) and high WSSR (WSSR≥4th quartile, aHR, 3.05; 95% CI, 1.25 to 7.41; p=0.014) were independently correlated with a higher risk of stroke relapse in the same territory.7 Based on the SOpHIA cohort, Tian *et al* developed a D2H2A nomogram to predict recurrent ischaemic stroke in the same territory in patients with sICAS.25 Diabetes, dyslipidaemia, haemodynamic status (PR and WSSR), hypertension and age ≥50 years were incorporated in the predictive model, which could be a useful tool to stratify patients with sICAS receiving medical treatment. Further, in a substudy of SOpHIA, Feng *et al* 26 divided 157 patients with 50%–99% sICAS into normal PR (PR>median) and low PR (PR≤median) groups and investigated the influence of PR on the association between systolic blood pressure (SBP) levels throughout follow-up (SBPFU) and the risk of recurrent stroke in the same territory, in medically treated patients with sICAS. They found patients with normal PR and lower SBPFU had a significantly decreased risk of recurrent stroke (HR for 10 mm Hg decrement, 0.46, 95% CI, 0.24 to 0.88; p=0.018); yet, patients with low PR and SBPFU≤130 mm Hg had an increased risk of recurrent stroke, relative to 130