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Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke
Xinyi Leng1, Fabien Scalzo2, Hing Lung Ip1
1Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China.
Insights
Computational fluid dynamics (CFD) models of intracranial atherosclerosis (ICAS) can predict stroke recurrence. Hemodynamic parameters like shear strain rate and velocity ratios are key indicators for patients with severe ICAS.
Area of Science:
- Neurology
- Medical Imaging
- Biomedical Engineering
Background:
- Patients with symptomatic intracranial atherosclerosis (ICAS) and severe stenosis (≥70%) face a high risk of recurrent stroke.
- Understanding the hemodynamic factors contributing to stroke recurrence in ICAS is crucial for risk stratification.
Purpose of the Study:
- To evaluate the relationship between hemodynamics of ICAS, derived from computational fluid dynamics (CFD) models, and the risk of recurrent stroke.
- To assess the predictive value of hemodynamic parameters in patients with severe symptomatic ICAS.
Main Methods:
- Patients with 70-99% symptomatic ICAS were enrolled.
- CFD models were created from computed tomographic angiography (CTA) images to analyze lesion hemodynamics.
- Key hemodynamic parameters included pressure, shear strain rate (SSR), and velocity ratios across the stenosis.
- Patients were followed for 1 year for recurrent stroke events.
Main Results:
- 32 patients were included; median age 65, 59.4% male.
- Higher SSR and velocity ratios across the ICAS lesion were significantly associated with recurrent ischemic stroke within 1 year (P=0.023 and P=0.035, respectively).
- Both SSR and velocity ratios demonstrated good predictive performance (c-statistics of 0.776).
Conclusions:
- Hemodynamic analysis using CFD models derived from routine CTA images can predict stroke recurrence in patients with severe symptomatic ICAS.
- These CFD-derived hemodynamic parameters offer a promising tool for identifying high-risk patients for targeted intervention.
Background:
Patients with symptomatic intracranial atherosclerosis (ICAS) of ≥ 70% luminal stenosis are at high risk of stroke recurrence. We aimed to evaluate the relationships between hemodynamics of ICAS revealed by computational fluid dynamics (CFD) models and risk of stroke recurrence in this patient subset.
Methods:
Patients with a symptomatic ICAS lesion of 70-99% luminal stenosis were screened and enrolled in this study. CFD models were reconstructed based on baseline computed tomographic angiography (CTA) source images, to reveal hemodynamics of the qualifying symptomatic ICAS lesions. Change of pressures across a lesion was represented by the ratio of post- and pre-stenotic pressures. Change of shear strain rates (SSR) across a lesion was represented by the ratio of SSRs at the stenotic throat and proximal normal vessel segment, similar for the change of flow velocities. Patients were followed up for 1 year.
Results:
Overall, 32 patients (median age 65; 59.4% males) were recruited. The median pressure, SSR and velocity ratios for the ICAS lesions were 0.40 (-2.46-0.79), 4.5 (2.2-20.6), and 7.4 (5.2-12.5), respectively. SSR ratio (hazard ratio [HR] 1.027; 95% confidence interval [CI], 1.004-1.051; P = 0.023) and velocity ratio (HR 1.029; 95% CI, 1.002-1.056; P = 0.035) were significantly related to recurrent territorial ischemic stroke within 1 year by univariate Cox regression, respectively with the c-statistics of 0.776 (95% CI, 0.594-0.903; P = 0.014) and 0.776 (95% CI, 0.594-0.903; P = 0.002) in receiver operating characteristic analysis.
Conclusions:
Hemodynamics of ICAS on CFD models reconstructed from routinely obtained CTA images may predict subsequent stroke recurrence in patients with a symptomatic ICAS lesion of 70-99% luminal stenosis.
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