scholarly journals Effects of progressive carotid stenosis on cerebral haemodynamics: aortic-cerebral 3D patient-specific simulation

2021 ◽  
Vol 15 (1) ◽  
pp. 830-847
Author(s):  
Taehak Kang ◽  
Debanjan Mukherjee ◽  
Jeong-Min Kim ◽  
Kwang-Yeol Park ◽  
Jaiyoung Ryu
2020 ◽  
Author(s):  
Joseph P Archie

AbstractIntroductionIn patients with 70% to 99% diameter carotid artery stenosis cerebral blood flow reserve may be protective of future ischemic cerebral events. Reserve cerebral blood flow is created by brain auto-regulation. Both cerebral blood flow reserve and cerebrovascular reactivity can be measured non-invasively. However, the factors and variables that determine the availability and magnitude and of reserve blood flow remain poorly understood. The availability of reserve cerebral blood flow is a predictor of stroke risk. The aim of this study is to employ a hemodynamic model to predict the variables and functional relationships that determine cerebral blood flow reserve in patients with significant carotid stenosis.MethodsA basic one-dimensional, three-unit (carotid, collateral and brain) energy conservation fluid mechanics blood flow model is employed. It has two distinct but adjacent blood flow components with normal cerebral blood flow at the interface. In the brain auto-regulated blood flow component cerebral blood flow is maintained normal by reserve flow. In the brain pressure dependent blood flow component cerebral blood flow is below normal because cerebral perfusion pressure is below the lower threshold value for auto-regulation. Patient specific values of collateral vascular resistance are determined from a model solution using clinically measured systemic and carotid arterial stump pressures. Collateral vascular resistance curves illustrate the model solutions for reserve and actual cerebral blood flow as a function of percent diameter carotid artery stenosis and mean systemic arterial pressure. The threshold cerebral perfusion pressure value for auto-regulation is assumed to be 50 mmHg. Normal auto-regulated regional cerebral blood flow is assumed to be 50 ml/min/100g. Cerebral blood flow and reserve blood flow solutions are given for systemic arterial pressures of 80, 90, 100, 110 and 120 mmHg and for three patient specific collateral vascular resistance values, Rw = 1.0 (mean patient value), Rw = 0.5 (lower 1 SD) and Rd = 3.0 (upper 1 SD).ResultsReserve cerebral blood flow is only available when a patients cerebral perfusion pressure is in the normal auto-regulatory range. Both actual and reserve cerebral blood flows are primarily from the carotid circulation when carotid stenosis is less than 60% diameter. Between 60% and 75% stenosis the remaining carotid blood flow reserve is utilized and at higher degrees of stenosis all reserve flow is from the collateral circulation. The primary independent variables that determine actual and reserve cerebral blood flow are mean systemic arterial pressure, degree of carotid stenosis and patient specific collateral vascular resistance. Approximate 16% of patients have collateral vascular resistance greater than 5.0 and are predicted to be at high risk of cerebral ischemia or infarction with progression to severe carotid stenosis or occlusion. The approximate 50% of patients with a collateral vascular resistance less than 1.0 are predicted to have adequate cerebral blood flow with progression to carotid occlusion, and most maintain some reserve. Clinically measured values of cerebral blood flow reserve or cerebrovascular reactivity are predicted to be unreliable without consideration of systemic arterial pressure and degree of carotid stenosis. Reserve cerebral blood flow values measured in patients with only moderate 60% to 70% carotid stenosis are in general too high and variable to be of clinical value, but are most reliable when measured near 80% diameter stenosis and considered as percent of the maximum reserve blood flow. Patient specific measured reserve blood flow values can be inserted into the model to calculate the collateral vascular resistance.ConclusionsPredicting cerebral blood flow reserve in patients with significant carotid stenosis is complex and multifactorial. A simple cerebrovascular model predicts that patient specific collateral vascular resistance is an excellent predictor of reserve cerebral blood flow in patients with significant carotid stenosis. Cerebral blood flow reserve measurements are of limited value without accounting for systemic pressure and actual percent carotid stenosis. Asymptomatic patients with severe carotid artery stenosis and a collateral vascular resistance greater than 1.0 are at increased risk of cerebral ischemia and may benefit from carotid endarterectomy.


2018 ◽  
Vol 24 (C) ◽  
pp. 76
Author(s):  
Viviana Mancini ◽  
Daniela Tommasin ◽  
Yanlu Li ◽  
Roel Baets ◽  
Stephen Greenwald ◽  
...  

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Shunichi Fukuda ◽  
Yuji Shimogonya

Introduction: There is still insufficient to determine which carotid stenosis is likely to progress. The carotid artery shape is an independent risk factor for intimal thickening. Although it is assumed that hemodynamic factors are strongly involved in the mechanisms, the details are unknown. Here, we removed carotid plaques in unilateral carotid stenotic cases, and reproduced the vessel shape without plaques as after carotid endarterectomy, and compared hemodynamic distributions with the non-stenotic side. Methods: We used 30 cases of unilateral carotid stenosis (area stenosis rate > 60%) registered in the National Hospital Organization Prospective Clinical Study; Carotid CFD Study. The plaques in DICOM images were artificially removed (Figure 1), and the vessel shape without plaque was reproduced. Patient-specific arterial geometries and inflow velocities were obtained from 3D-CTA and carotid doppler examinations.We compared distributions of hemodynamic indices (time-averaged wall shear stress (WSS), time-averaged WSS gradient, normalized WSS, normalized WSS gradient, OSI and NtransWSS) at 3 regions; the stenotic site, its proximal and distal sites (10 mm). Results and Conclusions: The average age was 71.6 years, male 23 cases, hypertension 20, diabetes 7, dyslipidemia 15, smoking history 22, and average area stenosis rate 72.6%. Normalized WSS was lower (p<0.0001, Wilcoxon signed rank test), and NtransWSS (p=0.0242) and OSI (p=0.0355) were higher in the stenotic sites of vessels after plaque removal (Figure 2). The data suggest that low and disturbed WSS caused by differences in carotid shape may contribute to the progress in stenosis at the carotid bifurcation.


2016 ◽  
Vol 311 (3) ◽  
pp. H645-H653 ◽  
Author(s):  
Xin Liu ◽  
Heye Zhang ◽  
Lijie Ren ◽  
Huahua Xiong ◽  
Zhifan Gao ◽  
...  

The functional assessment of a hemodynamic significant stenosis base on blood pressure variation has been applied for evaluation of the myocardial ischemic event. This functional assessment shows great potential for improving the accuracy of the classification of the severity of carotid stenosis. To explore the value of grading the stenosis using a pressure gradient (PG)—we had reconstructed patient-specific carotid geometries based on MRI images—computational fluid dynamics were performed to analyze the PG in their stenotic arteries. Doppler ultrasound image data and the corresponding MRI image data of 19 patients with carotid stenosis were collected. Based on these, 31 stenotic carotid arterial geometries were reconstructed. A combinatorial boundary condition method was implemented for steady-state computer fluid dynamics simulations. Anatomic parameters, including tortuosity (T), the angle of bifurcation, and the cross-sectional area of the remaining lumen, were collected to investigate the effect on the pressure distribution. The PG is highly correlated with the severe stenosis ( r = 0.902), whereas generally, the T and the angle of the bifurcation negatively correlate to the pressure drop of the internal carotid artery stenosis. The calculation required <10 min/case, which made it prepared for the fast diagnosis of the severe stenosis. According to the results, we had proposed a potential threshold value for distinguishing severe stenosis from mild-moderate stenosis (PG = 0.88). In conclusion, the PG could serve as the additional factor for improving the accuracy of grading the severity of the stenosis.


2021 ◽  
Vol 74 (3) ◽  
pp. e146
Author(s):  
Jonas Schollenberger ◽  
Nicholas Osborne ◽  
Luis Hernandez-Garcia ◽  
C. Alberto Figueroa

2021 ◽  
pp. 1-8
Author(s):  
Jiaqiu Wang ◽  
Jessica Benitez Mendieta ◽  
Phani Kumari Paritala ◽  
Yuqiao Xiang ◽  
Owen Christopher Raffel ◽  
...  

Background: Carotid atherosclerosis is one of the main underlying inducements of stroke, which is a leading cause of disability. The morphological feature and biomechanical environment have been found to play important roles in atherosclerotic plaque progression. However, the biomechanics in each patient’s blood vessel is complicated and unique. Method: To analyse the biomechanical risk of the patient-specific carotid stenosis, this study used the fluid-structure interaction (FSI) computational biomechanical model. This model coupled both structural and hemodynamic analysis. Two patients with carotid stenosis planned for carotid endarterectomy were included in this study. The 3D models of carotid bifurcation were reconstructed using our in-house-developed protocol based on multisequence magnetic resonance imaging (MRI) data. Patient-specific flow and pressure waveforms were used in the computational analysis. Multiple biomechanical risk factors including structural and hemodynamic stresses were employed in post-processing to assess the plaque vulnerability. Results: Significant difference in morphological and biomechanical conditions between 2 patients was observed. Patient I had a large lipid core and serve stenosis at carotid bulb. The stenosis changed the cross-sectional shape of the lumen. The blood flow pattern changed consequently and led to a complex biomechanical environment. The FSI results suggested a potential plaque progression may lead to a high-risk plaque, if no proper treatment was performed. The patient II had significant tandem stenosis at both common and internal carotid artery (CCA and ICA). From the results of biomechanical factors, both stenoses had a high potential of plaque progression. Especially for the plaque at ICA branch, the current 2 small plaques might further enlarge and merge as a large vulnerable plaque. The risk of plaque rupture would also increase. Conclusions: Computational biomechanical analysis is a useful tool to provide the biomechanical risk factors to help clinicians assess and predict the patient-specific plaque vulnerability. The FSI computational model coupling the structural and hemodynamic computational analysis, better replicates the in vivo biomechanical condition, which can provide multiple structural and flow-based risk factors to assess plaque vulnerability.


Author(s):  
joseph p archie

Joseph P Archie Jr, PhD, MD Abstract Purpose. Patients with 50% or greater diameter stenosis are at risk for ischemic stroke due to embolization and/or reduced cerebral blood flow. The hemodynamics of progressive carotid stenosis on cerebral blood flow and blood flow reserve has not been adequately measured or predicted. This information is needed for stroke risk stratification in patients with carotid stenosis. The aim of this hemodynamic model study is to predict the contribution of carotid and collateral blood flows to regional cerebral blood flow and cerebral blood flow reserve in patients with moderate to severe carotid stenosis. Methods. A one-dimensional three-parameter fluid mechanics model for the carotid, collateral and brain vascular systems is used to predict regional cerebral blood flow and blood flow reserve as a function of percent diameter carotid stenosis. The model is based on the principal of conservation of energy as employed by Bernoulli to describe fluid flow on a streamline. When applied to the human cerebrovascular system there are three vascular resistance components; carotid, collateral and brain. Carotid artery vascular resistance is assumed to be a function of fractional percent carotid artery area stenosis. This is not a complex modern computational fluid mechanics study. The model blood flow algebraic equations have simple solutions, one of which gives patient specific collateral resistance values. The solutions are given as patient specific cerebral blood flows and flow reserve as a function of percent diameter stenosis. Established normal clinical values of regional cerebral blood flow, cerebral blood flow auto-regulation and the lower threshold of cerebral perfusion pressure for cerebral auto-regulation are used. Carotid vascular resistance is assumed to be proportional to percent area carotid stenosis. Theoretical solutions use mean systemic arterial pressure of 100mmHg and key clinical values of patient collateral vascular resistance. Clinical solutions use patient measured systemic arterial pressures and carotid stump pressures. The solutions are given as patient specific cerebral blood flow and reserve cerebral blood flow curves over the range of diameter carotid stenosis. Results. Normal regional cerebral blood flow of 50ml/min/100g is predicted to be maintained up to 65% diameter carotid stenosis as reserve blood flow is reduced. With further progression of carotid stenosis to occlusion approximately half of patients are predicted to develop some reduction in cerebral blood flow. However, only about 20% of patients have a decrease in cerebral blood flow below the 30ml/min/100g threshold for cerebral ischemic symptoms. Approximately 10% of patients are predicted to develop regional cerebral blood flow less than the 18ml/min/100g threshold for irreversible ischemic injury. The model predicts critical carotid artery stenosis to be between 65% and 71% diameter depending on mean systemic arterial pressure. With higher degrees of stenosis carotid artery blood flow cannot maintain normal cerebral flow without the contribution of collateral flow. The predicted magnitude of carotid energy dissipation between 60% and 90% stenosis is consistent with observed cervical bruit intensity. Predicted patient specific cerebral blood flow reserve is adequate to prevent significant cerebral ischemia in the majority of patients. Conclusions. Patient specific collateral vascular resistance blood flow curves predict regional cerebral blood flow and blood flow reserve as a function of the degree of diameter carotid artery stenosis. The carotid component of cerebral blood flow is predicted to maintain normal cerebral blood flow up to a critical carotid diameter stenosis of 65% to 71%. Collateral blood flow is necessary to maintain normal cerebral flow at higher degrees of carotid stenosis. The clinical model predicts that many patients do not have sufficient collateral flow to prevent a decrease in cerebral flow should carotid stenosis progress to high grade or occlusion. However, only about 10% of patients are predicted to develop irreversible regional cerebral ischemic injury. Estimated carotid stenosis energy dissipation magnitudes agree with observed cervical bruit intensity. Correlation of predicted cerebral reserve blood flow curves with clinically measured cerebrovascular reactivity/reserve has the potential to predict the probability of future cerebral ischemia in asymptomatic patients with 60% to 80% stenosis.


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