A magnetic resonance imaging-based computational analysis of cerebral hemodynamics in patients with carotid artery stenosis

Management of asymptomatic carotid artery stenosis (CAS) relies on measuring the percentage of stenosis. The aim of this study was to investigate the impact of CAS on cerebral hemodynamics using magnetic resonance imaging (MRI)-informed computational fluid dynamics (CFD) and to provide novel hemodynamic metrics that may improve the understanding of stroke risk. CFD analysis was performed in two patients with similar degrees of asymptomatic high-grade CAS. Three-dimensional anatomical-based computational models of cervical and cerebral blood flow were constructed and calibrated patient-specifically using phase-contrast MRI flow and arterial spin labeling perfusion data. Differences in cerebral hemodynamics were assessed in preoperative and postoperative models. Preoperatively, patient 1 demonstrated large flow and pressure reductions in the stenosed internal carotid artery, while patient 2 demonstrated only minor reductions. Patient 1 exhibited a large amount of flow compensation between hemispheres (80.31%), whereas patient 2 exhibited only a small amount of collateral flow (20.05%). There were significant differences in the mean pressure gradient over the stenosis between patients preoperatively (26.3 vs. 1.8 mmHg). Carotid endarterectomy resulted in only minor hemodynamic changes in patient 2. MRI-informed CFD analysis of two patients with similar clinical classifications of stenosis revealed significant differences in hemodynamics which were not apparent from anatomical assessment alone. Moreover, revascularization of CAS might not always result in hemodynamic improvements. Further studies are needed to investigate the clinical impact of hemodynamic differences and how they pertain to stroke risk and clinical management.

Deep learning-based hemodynamic prediction of carotid artery stenosis before and after surgical treatments

Hemodynamic prediction of carotid artery stenosis (CAS) is of great clinical significance in the diagnosis, prevention, and treatment prognosis of ischemic strokes. While computational fluid dynamics (CFD) is recognized as a useful tool, it shows a crucial issue that the high computational costs are usually required for real-time simulations of complex blood flows. Given the powerful feature-extraction capabilities, the deep learning (DL) methodology has a high potential to implement the mapping of anatomic geometries and CFD-driven flow fields, which enables accomplishing fast and accurate hemodynamic prediction for clinical applications. Based on a brain/neck CT angiography database of 280 subjects, image based three-dimensional CFD models of CAS were constructed through blood vessel extraction, computational domain meshing and setting of the pulsatile flow boundary conditions; a series of CFD simulations were undertaken. A DL strategy was proposed and accomplished in terms of point cloud datasets and a DL network with dual sampling-analysis channels. This enables multimode mapping to construct the image-based geometries of CAS while predicting CFD-based hemodynamics based on training and testing datasets. The CFD simulation was validated with the mass flow rates at two outlets reasonably agreed with the published results. Comprehensive analysis and error evaluation revealed that the DL strategy enables uncovering the association between transient blood flow characteristics and artery cavity geometric information before and after surgical treatments of CAS. Compared with other methods, our DL-based model trained with more clinical data can reduce the computational cost by 7,200 times, while still demonstrating good accuracy (error<12.5%) and flow visualization in predicting the two hemodynamic parameters. In addition, the DL-based predictions were in good agreement with CFD simulations in terms of mean velocity in the stenotic region for both the preoperative and postoperative datasets. This study points to the capability and significance of the DL-based fast and accurate hemodynamic prediction of preoperative and postoperative CAS. For accomplishing real-time monitoring of surgical treatments, further improvements in the prediction accuracy and flexibility may be conducted by utilizing larger datasets with specific real surgical events such as stent intervention, adopting personalized boundary conditions, and optimizing the DL network.

Pentraxin 3, TNF-α, and LDL-C Are Associated With Carotid Artery Stenosis in Patients With Ischemic Stroke

Background: Carotid artery stenosis (CAS), typically resulting from atherosclerotic progression, is more common than intracranial atherosclerotic disease in patients with cerebrovascular disease. Prior literature has incompletely established the relationship of Pentraxin 3 (PTX3) and CAS complexity and severity. This study aims to more thoroughly evaluate the association of plasma PTX3 levels and the prevalence and severity of CAS in patients with cerebrovascular disease.

Methods: Two hundred and six patients with ischemic stroke underwent multiphase computerized tomography angiography (CTA) of the head and neck to assess the presence and severity of carotid artery stenosis. Patients were divided into groups with either no carotid artery stenosis (CAS-free) or carotid artery stenosis (CAS). The CAS group was further divided into groups based on the degree of stenosis and the number of involved vessels. The PTX3 and Tumor Necrosis Factor-alpha (TNF-α) concentration were measured by ELISA.

Results: Plasma levels of PTX3, TNF-α, and low-density lipoprotein cholesterol (LDL-C) were increased significantly in the CAS group patients vs. the CAS-free group (p = 0.000, 0.002, 0.002, respectively). Within the CAS group, PTX3, TNF-α, and LDL-C were significantly elevated in stenosis of ≥50% group compared to <50% group (p = 0.001, 0.002, 0.049, respectively). The multivariate logistic binary regression analysis revealed that increased age, elevated levels of PTX3, LDL-C, and TNF-α were all independent risk factors for occurrence of carotid stenosis. PTX3 level correlated with the severity of carotid stenosis.

Conclusions: High plasma PTX3 levels, TNF-α, and LDL-C are significantly correlated with the prevalence and severity of carotid artery stenosis. PTX3 may be a more powerful predictor for the severity of carotid artery stenosis.

Progression of asymptomatic mild carotid artery stenosis: Implications for frequency of surveillance

We looked retrospectively at the 3- to 5-year progression of mild, asymptomatic carotid artery stenosis (CAS). A random sample of 600 patients who had undergone at least two carotid artery duplex ultrasounds between 31 October 2006 and 1 November 2016 with a second duplex ⩾3 and ⩽5 years following the initial one were screened for inclusion. Internal carotid arteries (ICAs) were included if they had 20-49% stenosis on the initial duplex, with 440 carotid arteries meeting this criteria. Analyses were performed utilizing chi-squared and two-tailed t-tests. Twenty-four (5.45%) of the initial 440 carotid arteries progressed to moderate CAS. There was a statistically significant increase in the prevalence of hypertension (68% vs 47%, p=0.022) and diabetes mellitus (44% vs 22%, p=0.008) in patients with carotids that progressed to moderate CAS. There was a decrease in moderate-intensity statin use (32% vs 58%, p=0.005) and an increase in patients not on statins (36% vs 11%, p=0.001) in the group of carotids that progressed to moderate CAS. One carotid artery (0.2%) progressed from mild CAS to severe CAS. If supported by others, our data may lead to a change in the recommendations regarding appropriate follow-up of asymptomatic CAS.

Prevalence of carotid artery stenosis in Chinese patients with angina pectoris

BACKGROUND

The prevalence of carotid artery stenosis (CAS) in Chinese patients with angina pectoris is unknown.

METHODS

The study population consisted of 989 consecutive patients who were scheduled to undergo nonemergent coronary angiography for suspicion of coronary artery disease (CAD) because of angina pectoris between January 2013 and December 2014. All patients underwent carotid ultrasonography to screen for CAS within one month before or after coronary angiography. We defined cases with 0-50%, 50%-70%, and >70% stenosis as mild, moderate, and severe stenosis, respectively.

RESULTS

CAD was presented in 853 patients (86.2%) of whom 191 patients (19.3%) had 1-vessel disease, 246 patients (24.9%) had 2-vessel disease and 416 patients (42.1%) had 3-vessel disease; left main trunk stenosis present in 137 patients (13.9%). In carotid ultrasonography, the prevalence of mild, moderate, and severe stenosis as well as that of total occlusion of the carotid artery was 54.5%, 13%, 4.7% and 0.8%, respectively. Significant CAS (>50% stenosis and total occlusion) was present in 10.3%, 13.9%, 19.9% and 22.8% of patients with 0-vessel, 1-vessel, 2-vessel and 3-vessel CAD. The severity of CAS was directly correlated (r=0.194, P<0.001) with the extent of CAD. The independent predictors of severe CAS and total carotid artery occlusion were increased age, male sex, hypertension, diabetes mellitus, hyperhomocysteinemia, a previous history of stroke and 3-vessel CAD.

CONCLUSIONS

The prevalence of CAS was not rare in China when compared with that in western countries, and the presence of CAS was weakly correlated with the extent of CAD. Screening for CAS should be recommended in Chinese patients with CAD, especially in those with one or more CAS-associated risk factors.