Computational fluid dynamics of computed tomography angiography to detect the hemodynamic impact of intracranial atherosclerotic stenosis

Multimodal imaging approach for the diagnosis of intracranial atherosclerotic disease (ICAD): Basic principles, current and future perspectives

PURPOSE

To review the different imaging modalities utilized in the diagnosis of Intracranial Atherosclerotic Disease (ICAD) including their latest development and relevance in management of ICAD.

METHODS

A review of the literature was conducted through a search in google scholar, PubMed/Medline, EMBASE, Scopus, clinical trials.gov and the Cochrane Library. Search terms included, "imaging modalities in ICAD," "ICAD diagnostic," "Neuroimaging of ICAD," "Evaluation of ICAD". A summary and comparison of each modality's basic principles, advantages and disadvantages were included.

RESULTS

A total of 144 articles were identified and reviewed. The most common imaging used in ICAD diagnoses were DSA, CTA, MRA and TCD. They all had proven accuracy, their own benefits, and limitations. Newer modalities such as VWI, IVUS, OCT, PWI and CFD provide more detailed information regarding the vessel walls, plaque characteristics, and flow dynamics, which play a tremendous role in treatment guidance. In certain clinical scenarios, using more than one modality has been shown to be helpful in ICAD identification. The rapidly evolving software related to imaging studies, such as virtual histology, are very promising for the diagnostic and management of ICAD.

CONCLUSIONS

ICAD is a common cause of recurrent ischemic stroke. Its management can be both medical and/or procedural. Many different imaging modalities are used in its diagnosis. In certain clinical scenario, a combination of two more modalities can be critical in the management of ICAD. We expect that continuous development of imaging technique will lead to individualized and less invasive management with adequate outcome.

Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario

Carotid artery stenosis is a major cause of morbidity and mortality. The journey to understanding carotid disease has developed over time and radiology has a pivotal role in diagnosis, risk stratification and therapeutic management. This paper reviews the history of diagnostic imaging in carotid disease, its evolution towards its current applications in the clinical and research fields, and the potential of new technologies to aid clinicians in identifying the disease and tailoring medical and surgical treatment.

Functional Assessment of Cerebral Artery Stenosis by Angiography-Based Quantitative Flow Ratio: A Pilot Study

Background

Increasing attention has been paid to the hemodynamic evaluation of cerebral arterial stenosis. We aimed to demonstrate the performance of angiography-based quantitative flow ratio (QFR) to assess hemodynamic alterations caused by luminal stenoses, using invasive fractional pressure ratios (FPRs) as a reference standard.

Methods

Between March 2013 and December 2019, 29 patients undergoing the pressure gradient measurement of cerebral atherosclerosis were retrospectively enrolled. Wire-based FPR was defined by the arterial pressure distal to the stenotic lesion (Pd) to proximal (Pa) pressure ratios (Pd/Pa). FPR < 0.70 or FPR < 0.75 was assumed as hemodynamically significant stenosis. The new method of computing QFR from a single angiographic view, i.e., the Murray law-based QFR, was applied to the interrogated vessel. An artificial intelligence algorithm was developed to realize the automatic delineation of vascular contour.

Results

Fractional pressure ratio and QFR were assessed in 38 vessels from 29 patients. Excellent correlation and agreement were observed between QFR and FPR [r = 0.879, P < 0.001; mean difference (bias): −0.006, 95% limits of agreement: −0.198 to 0.209, respectively). Intra-observer and inter-observer reliability in QFR were excellent (intra-class correlation coefficients, 0.996 and 0.973, respectively). For predicting FPR < 0.70, the area under the receiver-operating characteristic curves (AUC) of QFR was 0.946 (95% CI, 0.820 to 0.993%). The sensitivity and specificity of QFR < 0.70 for identifying FPR < 0.70 was 88.9% (95% CI, 65.3 to 98.6%) and 85.0% (95% CI, 62.1 to 96.8%). For predicting FPR < 0.75, QFR showed similar performance with an AUC equal to 0.926.

Conclusion

Computational QFR from a single angiographic view achieved comparable results to the wire-based FPR. The excellent diagnostic performance and repeatability empower QFR with high feasibility in the functional assessment of cerebral arterial stenosis.

Computational Fluid Dynamics in Intracranial Atherosclerosis - Lessons from Cardiology: A Review of CFD in Intracranial Atherosclerosis

BACKGROUND

Intracranial atherosclerosis is a common cause of stroke with a high recurrence rate. Haemodynamically significant lesions are associated with a particularly high risk of recurrence. Computational fluid dynamics (CFD) is a tool that has been investigated to identify haemodynamically significant lesions. CFD in the intracranial vasculature benefits from the precedent set by cardiology, where CFD is an established clinical tool. This precedent is particularly important in CFD as models are very heterogenous. There are many decisions-points in the model-creation process, usually involving a trade-off between computational expense and accuracy.

OBJECTIVES

This study aimed to review published CFD models in intracranial atherosclerosis and compare them to those used in cardiology.

METHODS

A systematic search for all published computational fluid dynamics models applied to intracranial atherosclerosis was performed. Each study was analysed as regards to the different steps in creating a fluid dynamics model and findings were compared with established cardiology CFD models.

RESULTS AND CONCLUSION

38 papers were screened and 12 were included in the final analysis. There were important differences between coronary and intracranial atherosclerosis models in the following areas: area of interest segmented, use of transient models vs steady-state models, boundary conditions, methods for solving the fluid dynamics equations and validation. These differences may be high-yield areas to explore for future research.

Sustaining cerebral perfusion in intracranial atherosclerotic stenosis: The roles of antegrade residual flow and leptomeningeal collateral flow

We aimed to investigate the roles of antegrade residual flow and leptomeningeal collateral flow in sustaining cerebral perfusion distal to an intracranial atherosclerotic stenosis (ICAS). Patients with apparently normal cerebral perfusion distal to a symptomatic middle cerebral artery (MCA)-M1 stenosis were enrolled. Computational fluid dynamics models were built based on CT angiography to obtain a translesional pressure ratio (PR) to gauge the residual antegrade flow. Leptomeningeal collaterals (LMCs) were scaled on CT angiography. Cerebral perfusion metrics were obtained in CT perfusion maps. Among 83 patients, linear regression analyses revealed that both translesional PR and LMC scale were independently associated with relative ipsilesional mean transit time (rMTT). Subgroup analyses showed that ipsilesional rMTT was significantly associated with translesional PR (p < 0.001) rather than LMC scale in those with a moderate (50-69%) MCA stenosis, which, however, was only significantly associated with LMC scale (p = 0.051) in those with a severe (70-99%) stenosis. Antegrade residual flow and leptomeningeal collateral flow have complementary effects in sustaining cerebral perfusion distal to an ICAS, while cerebral perfusion may rely more on the collateral circulation in those with a severe stenosis.

Hemodynamics and stroke risk in intracranial atherosclerotic disease

OBJECTIVE

To investigate whether hemodynamic features of symptomatic intracranial atherosclerotic stenosis (sICAS) might correlate with the risk of stroke relapse, using a computational fluid dynamics (CFD) model.

METHODS

In a cohort study, we recruited patients with acute ischemic stroke attributed to 50 to 99% ICAS confirmed by computed tomographic angiography (CTA). With CTA-based CFD models, translesional pressure ratio (PR = pressure_poststenotic /pressure_prestenotic ) and translesional wall shear stress ratio (WSSR = WSS_{stenotic - throat} /WSS_prestenotic ) were obtained in each sICAS lesion. Translesional PR ≤ median was defined as low PR and WSSR ≥4th quartile as high WSSR. All patients received standard medical treatment. The primary outcome was recurrent ischemic stroke in the same territory (SIT) within 1 year.

RESULTS

Overall, 245 patients (median age = 61 years, 63.7% males) were analyzed. Median translesional PR was 0.94 (interquartile range [IQR] = 0.87-0.97); median translesional WSSR was 13.3 (IQR = 7.0-26.7). SIT occurred in 20 (8.2%) patients, mostly with multiple infarcts in the border zone and/or cortical regions. In multivariate Cox regression, low PR (adjusted hazard ratio [HR] = 3.16, p = 0.026) and high WSSR (adjusted HR = 3.05, p = 0.014) were independently associated with SIT. Patients with both low PR and high WSSR had significantly higher risk of SIT than those with normal PR and WSSR (risk = 17.5% vs 3.0%, adjusted HR = 7.52, p = 0.004).

INTERPRETATION

This work represents a step forward in utilizing computational flow simulation techniques in studying intracranial atherosclerotic disease. It reveals a hemodynamic pattern of sICAS that is more prone to stroke relapse, and supports hypoperfusion and artery-to-artery embolism as common mechanisms of ischemic stroke in such patients. Ann Neurol 2019;85:752-764.

Semi-automated analysis of 4D flow MRI to assess the hemodynamic impact of intracranial atherosclerotic disease

PURPOSE

This study evaluated the feasibility of using 4D flow MRI and a semi-automated analysis tool to assess the hemodynamic impact of intracranial atherosclerotic disease (ICAD). The ICAD impact was investigated by evaluating pressure drop (PD) at the atherosclerotic stenosis and changes in cerebral blood flow distribution in patients compared to healthy controls.

METHODS

Dual-venc 4D flow MRI was acquired in 25 healthy volunteers and 16 ICAD patients (ICA, N = 3; MCA, N = 13) with mild (<50%), moderate (50-69%), or severe (>70%) intracranial stenosis. A semi-automated analysis tool was developed to quantify velocity and flow from 4D flow MRI and to evaluate cerebral blood flow redistribution. PD at stenosis was estimated using the Bernoulli equation. The PD calculation was examined by an in vitro phantom study against flow simulations.

RESULTS

Flow analysis in controls indicated symmetry in blood flow rate (FR) and peak velocity (PV) between the brain hemispheres. For patients, PV in the affected hemisphere was significantly (65%) higher than the normal side (P = 0.002). However, FR to both hemispheres of the brain was the same. The PD depicted significant correlation with PV asymmetry in patients (ρ = 0.67 and P = 0.02), and it was significantly higher for severe compared to moderate stenosis (3.73 vs. 2.30 mm Hg, P = 0.02).

CONCLUSION

4D flow MRI quantification enables assessment of the hemodynamic impact of ICAD. The significant difference of the PD between patients with severe and moderate stenosis and its correlation with PV asymmetry suggest that PD may be a pertinent hemodynamic biomarker to evaluate ICAD.

SIMULATION ANALYSIS OF BLOOD FLOW IN ARTERIES OF THE HUMAN ARM

Arteries in the upper limb play important roles in the circulation system of the human body. In particular, the radial artery has received considerable attention in traditional Chinese medicine for thousands of years. Here, a 3D model for the arm arteries has been created uncomplicated, in a Chinese adult's left hand, from the magnetic resonance imaging data, using professional modeling software to restore the basic structure of the arm artery in human body, before being imported to Ansys software for simulation. Blood model has been only simulated, and using the blood density of constant parameter and viscosity using the Carreau fluid model, and using viscous-laminar model of Fluent to obtain the velocity profile, static pressure and shear stress in the brachial, interosseous, ulnar, radial and palmar arch arteries. In particular, the brachial and bifurcations have the high pressure and velocity profiles. The simulation results obtained here are also validated by those published in the literature and proved the ulnar artery prevails over the radial artery as a blood supplier to the vessels in the wrist and hand.

Similarity Metric Learning for 2D to 3D Registration of Brain Vasculature

2D to 3D image registration techniques are useful in the treatment of neurological diseases such as stroke. Image registration can aid physicians and neurosurgeons in the visualization of the brain for treatment planning, provide 3D information during treatment, and enable serial comparisons. In the context of stroke, image registration is challenged by the occluded vessels and deformed anatomy due to the ischemic process. In this paper, we present an algorithm to register 2D digital subtraction angiography (DSA) with 3D magnetic resonance angiography (MRA) based upon local point cloud descriptors. The similarity between these local descriptors is learned using a machine learning algorithm, allowing flexibility in the matching process. In our experiments, the error rate of 2D/3D registration using our machine learning similarity metric (52.29) shows significant improvement when compared to a Euclidean metric (152.54). The proposed similarity metric is versatile and could be applied to a wide range of 2D/3D registration.