Noninvasive fractional flow in intracranial atherosclerotic stenosis: Reproducibility, limitations, and perspectives

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.

A Novel Spectral Index for Tracking Preload Change from a Wireless, Wearable Doppler Ultrasound

A wireless, wearable Doppler ultrasound offers a new paradigm for linking physiology to resuscitation medicine. To this end, the image analysis of simultaneously-acquired venous and arterial Doppler spectrograms attained by wearable ultrasound represents a new source of hemodynamic data. Previous investigators have reported a direct relationship between the central venous pressure (CVP) and the ratio of the internal jugular-to-common carotid artery diameters. Because Doppler power is directly related to the number of red cell scatterers within a vessel, we hypothesized that (1) the ratio of internal jugular-to-carotid artery Doppler power (V/A_POWER) would be a surrogate for the ratio of the vascular areas of these two vessels and (2) the V/A_POWER would track the anticipated CVP change during simulated hemorrhage and resuscitation. To illustrate this proof-of-principle, we compared the change in V/A_POWER obtained via a wireless, wearable Doppler ultrasound to B-mode ultrasound images during a head-down tilt. Additionally, we elucidated the change in the V/A_POWER during simulated hemorrhage and transfusion via lower body negative pressure (LBNP) and release. With these Interesting Images, we show that the Doppler V/A_POWER ratio qualitatively tracks anticipated changes in CVP (e.g., cardiac preload) which is promising for both diagnosis and management of hemodynamic unrest.

Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the "black-box" nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients' risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

Risk stratification in symptomatic intracranial atherosclerotic disease with conventional vascular risk factors and cerebral haemodynamics

BACKGROUND AND PURPOSE

Symptomatic intracranial atherosclerotic stenosis (sICAS) is associated with a considerable risk of recurrent stroke despite contemporarily optimal medical treatment. Severity of luminal stenosis in sICAS and its haemodynamic significance quantified with computational fluid dynamics (CFD) models were associated with the risk of stroke recurrence. We aimed to develop and compare stroke risk prediction nomograms in sICAS, based on vascular risk factors and these metrics.

METHODS

Patients with 50%-99% sICAS confirmed in CT angiography (CTA) were enrolled. Conventional vascular risk factors were collected. Severity of luminal stenosis in sICAS was dichotomised as moderate (50%-69%) and severe (70%-99%). Translesional pressure ratio (PR) and wall shear stress ratio (WSSR) were quantified via CTA-based CFD modelling; the haemodynamic status of sICAS was classified as normal (normal PR&WSSR), intermediate (otherwise) and abnormal (abnormal PR&WSSR). All patients received guideline-recommended medical treatment. We developed and compared performance of nomograms composed of these variables and independent predictors identified in multivariate logistic regression, in predicting the primary outcome, recurrent ischaemic stroke in the same territory (SIT) within 1 year.

RESULTS

Among 245 sICAS patients, 20 (8.2%) had SIT. The D₂H₂A nomogram, incorporating diabetes, dyslipidaemia, haemodynamic status of sICAS, hypertension and age ≥50 years, showed good calibration (P for Hosmer-Lemeshow test=0.560) and discrimination (C-statistic 0.73, 95% CI 0.60 to 0.85). It also had better performance in risk reclassification and provided larger net benefits in decision curve analysis, compared with nomograms composed of conventional vascular risk factors only, and plus the severity of luminal stenosis in sICAS. Sensitivity analysis in patients with anterior-circulation sICAS showed similar results.

CONCLUSIONS

The D₂H₂A nomogram, incorporating conventional vascular risk factors and the haemodynamic significance of sICAS as assessed in CFD models, could be a useful tool to stratify sICAS patients for the risk of recurrent stroke under contemporarily optimal medical treatment.

The Quantitative Associations Between Near Infrared Spectroscopic Cerebrovascular Metrics and Cerebral Blood Flow: A Scoping Review of the Human and Animal Literature

Cerebral blood flow (CBF) is an important physiologic parameter that is vital for proper cerebral function and recovery. Current widely accepted methods of measuring CBF are cumbersome, invasive, or have poor spatial or temporal resolution. Near infrared spectroscopy (NIRS) based measures of cerebrovascular physiology may provide a means of non-invasively, topographically, and continuously measuring CBF. We performed a systematically conducted scoping review of the available literature examining the quantitative relationship between NIRS-based cerebrovascular metrics and CBF. We found that continuous-wave NIRS (CW-NIRS) was the most examined modality with dynamic contrast enhanced NIRS (DCE-NIRS) being the next most common. Fewer studies assessed diffuse correlation spectroscopy (DCS) and frequency resolved NIRS (FR-NIRS). We did not find studies examining the relationship between time-resolved NIRS (TR-NIRS) based metrics and CBF. Studies were most frequently conducted in humans and animal studies mostly utilized large animal models. The identified studies almost exclusively used a Pearson correlation analysis. Much of the literature supported a positive linear relationship between changes in CW-NIRS based metrics, particularly regional cerebral oxygen saturation (rSO2), and changes in CBF. Linear relationships were also identified between other NIRS based modalities and CBF, however, further validation is needed.

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.

Endothelial Shear Stress and Platelet FcγRIIa Expression in Intracranial Atherosclerotic Disease

Intracranial atherosclerotic disease (ICAD) has been characterized by the degree of arterial stenosis and downstream hypoperfusion, yet microscopic derangements of endothelial shear stress at the luminal wall may be key determinants of plaque growth, vascular remodeling and thrombosis that culminate in recurrent stroke. Platelet interactions have similarly been a principal focus of treatment, however, the mechanistic basis of anti-platelet strategies is largely extrapolated rather than directly investigated in ICAD. Platelet FcγRIIa expression has been identified as a potent risk factor in cardiovascular disease, as elevated expression markedly increases the risk of recurrent events. Differential activation of the platelet FcγRIIa receptor may also explain the variable response of individual patients to anti-platelet medications. We review existing data on endothelial shear stress and potential interactions with the platelet FcγRIIa receptor that may alter the evolving impact of ICAD, based on local pathophysiology at the site of arterial stenosis. Current methods for quantification of endothelial shear stress and platelet activation are described, including tools that may be readily adapted to the clinical realm for further understanding of ICAD.

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.

Translesional pressure gradient and leptomeningeal collateral status in symptomatic middle cerebral artery stenosis

BACKGROUND AND PURPOSE

Leptomeningeal collateral (LMC) status governs the prognosis of large artery occlusive stroke, although factors determining LMC status are not fully elucidated. The aim was to investigate metrics affecting LMC status in such patients by using computational fluid dynamics (CFD) models based on computed tomography angiography (CTA).

METHODS

In this cross-sectional study, patients with recent ischaemic stroke or transient ischaemic attack attributed to atherosclerotic M1 middle cerebral artery (MCA) stenosis (50%-99%) were recruited. Demographic, clinical and imaging data of these patients were collected. Ipsilesional LMC status was graded as good or poor by assessing the laterality of anterior and posterior cerebral arteries in CTA. A CFD model based on CTA was constructed to reflect focal hemodynamics in the distal internal carotid artery, M1 MCA and A1 anterior cerebral artery. Pressure gradients were calculated across culprit MCA stenotic lesions in CFD models. Predictors for good LMC status were sought in univariate and multivariate analyses.

RESULTS

Amongst the 85 patients enrolled (mean age 61.5 ± 10.9 years), 38 (44.7%) had good ipsilesional LMC status. The mean pressure gradient across MCA lesions was 14.8 ± 18.1 mmHg. Advanced age (P = 0.030) and a larger translesional pressure gradient (P = 0.029) independently predicted good LMCs. A lower fasting blood glucose level also showed a trend for good LMCs (P = 0.058).

CONCLUSIONS

Our study suggested a correlation between translesional pressure gradient and maturation of LMCs in intracranial atherosclerotic disease. Further studies with more exquisite and dynamic monitoring of cerebral hemodynamics and LMC evolution are needed to verify the current findings.