The role of imaging in acute ischemic stroke

Multi-Level Biomarkers for Early Diagnosis of Ischaemic Stroke: A Systematic Review and Meta-Analysis

Blood biomarkers hold potential for the early diagnosis of ischaemic stroke (IS). We aimed to evaluate the current weight of evidence and identify potential biomarkers and biological pathways for further investigation. We searched PubMed, EMBASE, the Cochrane Library and Web of Science, used R package meta4diag for diagnostic meta-analysis and applied Gene Ontology (GO) analysis to identify vital biological processes (BPs). Among 8544 studies, we included 182 articles with a total of 30,446 participants: 15675 IS, 2317 haemorrhagic stroke (HS), 1798 stroke mimics, 846 transient ischaemic attack and 9810 control subjects. There were 518 pooled biomarkers including 203 proteins, 114 genes, 108 metabolites and 88 transcripts. Our study generated two shortlists of biomarkers for future research: one with optimal diagnostic performance and another with low selection bias. Glial fibrillary acidic protein was eligible for diagnostic meta-analysis, with summary sensitivities and specificities for differentiating HS from IS between 3 h and 24 h after stroke onset ranging from 73% to 80% and 77% to 97%, respectively. GO analysis revealed the top five BPs associated with IS. This study provides a holistic view of early diagnostic biomarkers in IS. Two shortlists of biomarkers and five BPs warrant future investigation.

Cerebellar Infarct Accompanied by Acute Hydrocephalus: A Case Report of 1-Year Follow-up in Rural Neurosurgical Practice

Cerebellar infarctions account for about 2-3% of all ischemic strokes, and acute hydrocephalus due to brainstem compression or compression of the cerebrospinal fluid (CSF) flows is a rare manifestation from a stroke of the posterior circulation. The condition is considered one of the most life-threatening complications in cerebellar infarct due to the possibility of transforaminal and upward transtentorial herniation. The management of patients with cerebellar infarct is challenging, because the patient usually presents with non-specific signs and symptoms until the patient loses consciousness. Standard management should be provided by a stroke unit team or neuro-intensive care unit. The precision timing of treatment and evaluation with close observation is crucial, even when there is no life-threatening condition at initial presentation, but sometimes it is difficult to fulfill in rural areas due to the substandard facilities and lack of resources. Here we report a case of cerebellar infarct with massive edema in association with acute hydrocephalus with the progressive deterioration that happened in a rural area. A 59-year-old male patient complained about an episode of sudden headache which was followed by dizziness, vomiting, and loss of balance. A head non-contrast CT scan in the emergency room (ER) is performed 4 hours after ictus, showed a slightly hypodense lesion in the left cerebellum, without accompanying edema and hydrocephalus. The patient was then managed conservatively in the ward. In the next 36 hours, his consciousness level was reduced and a head CT scan evaluation showed the development of massive edema of cerebellar infarct with acute hydrocephalus. The patient underwent an emergency surgical procedure with suboccipital decompressive craniectomy (SDC) with strokectomy, expanded duraplasty, and ventricular drainage (ventriculoperitoneal shunt). Satisfactory results with rapid resolution of GCS was seen at daily follow-up after surgery. A 1-year follow-up also showed remarkable outcomes.

Difference of Thrombus Location between Initial Noninvasive Vascular Image and First DSA Findings in Mechanical Thrombectomy for Intracranial Large Vessel Occlusion: Post Hoc Analysis of the SKIP Study

In patients who undergo mechanical thrombectomy for intracranial large vessel occlusion, the occluded site is sometimes distal to the site shown in the initial vascular imaging. We investigated the factors related to the change in the occluded site between the sequential imagings. The 203 patients in the SKIP study were reviewed retrospectively. Magnetic resonance angiography (MRA) or computed tomography angiography (CTA) was used to assess the occluded site. The occluded site shown in the cerebral angiography appeared to be distal to the occluded site shown in the initial vascular imaging in 55 patients (group A). The location of the occluded site in the remaining 148 patients did not change between the sequential imagings (group B). MRA was used more often than CTA in group A (54 MRA, 1 CTA; P <0.01). Patients with middle cerebral artery (M1) occlusion were more likely to show change of the occluded site than patients with internal carotid artery (ICA) occlusion (M1: 38%, ICA: 9%; P <0.01). The number of patients who received intravenous recombinant tissue plasminogen activator did not differ between the two groups (group A: 54%, group B: 49%; P = 0.5). In patients with acute intracranial large vessel occlusion who require mechanical thrombectomy, physicians should be aware that the location of the thrombus may be distal to the occluded site shown in the initial vascular imaging, particularly in patients with M1 occlusion shown by MRA.

The Stroke Neuro-Imaging Phenotype Repository: An Open Data Science Platform for Stroke Research

Stroke is one of the leading causes of death and disability worldwide. Reducing this disease burden through drug discovery and evaluation of stroke patient outcomes requires broader characterization of stroke pathophysiology, yet the underlying biologic and genetic factors contributing to outcomes are largely unknown. Remedying this critical knowledge gap requires deeper phenotyping, including large-scale integration of demographic, clinical, genomic, and imaging features. Such big data approaches will be facilitated by developing and running processing pipelines to extract stroke-related phenotypes at large scale. Millions of stroke patients undergo routine brain imaging each year, capturing a rich set of data on stroke-related injury and outcomes. The Stroke Neuroimaging Phenotype Repository (SNIPR) was developed as a multi-center centralized imaging repository of clinical computed tomography (CT) and magnetic resonance imaging (MRI) scans from stroke patients worldwide, based on the open source XNAT imaging informatics platform. The aims of this repository are to: (i) store, manage, process, and facilitate sharing of high-value stroke imaging data sets, (ii) implement containerized automated computational methods to extract image characteristics and disease-specific features from contributed images, (iii) facilitate integration of imaging, genomic, and clinical data to perform large-scale analysis of complications after stroke; and (iv) develop SNIPR as a collaborative platform aimed at both data scientists and clinical investigators. Currently, SNIPR hosts research projects encompassing ischemic and hemorrhagic stroke, with data from 2,246 subjects, and 6,149 imaging sessions from Washington University's clinical image archive as well as contributions from collaborators in different countries, including Finland, Poland, and Spain. Moreover, we have extended the XNAT data model to include relevant clinical features, including subject demographics, stroke severity (NIH Stroke Scale), stroke subtype (using TOAST classification), and outcome [modified Rankin Scale (mRS)]. Image processing pipelines are deployed on SNIPR using containerized modules, which facilitate replicability at a large scale. The first such pipeline identifies axial brain CT scans from DICOM header data and image data using a meta deep learning scan classifier, registers serial scans to an atlas, segments tissue compartments, and calculates CSF volume. The resulting volume can be used to quantify the progression of cerebral edema after ischemic stroke. SNIPR thus enables the development and validation of pipelines to automatically extract imaging phenotypes and couple them with clinical data with the overarching aim of enabling a broad understanding of stroke progression and outcomes.

Controversies in Imaging of Patients with Acute Ischemic Stroke: AJR Expert Panel Narrative Review

The development of reperfusion therapies has profoundly impacted stroke care, initially with the advent of IV thrombolytic (IVT) treatment and, more recently, with the development and refinement of endovascular treatment (EVT). Progress in neuroimaging has supported the paradigm shift of stroke care, and advanced neuroimaging now has a fundamental role in triaging patients for both IVT and EVT. As the standard of care for acute ischemic stroke (AIS) evolves, controversies remain in certain clinical scenarios. This article explores the use of multimodality imaging for treatment selection of AIS in the context of recent guidelines, highlighting controversial topics and providing guidance for clinical practice. Results of major randomized trials supporting EVT are reviewed. Advantages and disadvantages of CT, CTA, MRI, and MRA in stroke diagnosis are summarized, with attention to level 1 evidence supporting the role of vascular imaging and perfusion imaging. Patient selection is compared between approaches based on time thresholds and physiologic approaches based on infarct core measurement using imaging. Moreover, various imaging approaches to core measurement are described. As ongoing studies push treatment boundaries, advanced imaging is expected to help identify a widening range of patients who may benefit from therapy.

Multimodality Imaging in Acute Ischemic Stroke

Stroke is the most common cause of mortality and morbidity worldwide. The prognosis of stroke depends upon the area affected and its early treatment. Time is of the essence in the care of stroke patients as it is estimated that approximately 1.9 million neurons, 14 billion synapses, and 12 km myelinated nerve fibers are lost per minute. Therefore, early diagnosis and prompt treatment are necessary. The primary goal of imaging in acute stroke is to diagnose the underlying cause, estimate the area affected, predict response towards thrombolytic therapy and to exclude the conditions mimicking stroke. With advancements in radiology, multiple imaging modalities are available for diagnosis and predicting prognosis. None of them is considered alone to be perfect. In this era of multimodality imaging, the decision of choosing appropriate techniques depends upon purpose and availability. Non-Contrast Computed Tomography is time effective, and helps in excluding other causes, Trans Cranial Doppler is time-effective and cost-effective with wide availability, however, is operator dependent and less sensitive. It holds a great future in sonothrombolysis. Magnetic Resonance Imaging is so far considered to be the most superior one in terms of early diagnosis, planning for interventional treatment and predicting the response of treatment. However, it is limited due to high cost and lack of availability. The current review gives a detailed account of all imaging modalities available for imaging stroke and their associated pros and cons.

Deep symmetric three-dimensional convolutional neural networks for identifying acute ischemic stroke via diffusion-weighted images

BACKGROUND

Acute ischemic stroke (AIS) results in high morbidity, disability, and mortality. Early and automatic diagnosis of AIS can help clinicians administer the appropriate interventions.

OBJECTIVE

To develop a deep symmetric 3D convolutional neural network (DeepSym-3D-CNN) for automated AIS diagnosis via diffusion-weighted imaging (DWI) images.

METHODS

This study includes 190 study subjects (97 AIS and 93 Non-AIS) by collecting both DWI and Apparent Diffusion Coefficient (ADC) images. 3D DWI brain images are split into left and right hemispheres and input into two paths. A map with 125×253×14×12 features is extracted by each path of Inception Modules. After the features computed from two paths are subtracted through L-2 normalization, four multi-scale convolution layers produce the final predation. Three comparative models using DWI images including MedicalNet with transfer learning, Simple DeepSym-3D-CNN (each 3D Inception Module is replaced by a simple 3D-CNN layer), and L-1 DeepSym-3D-CNN (L-2 normalization is replaced by L-1 normalization) are constructed. Moreover, using ADC images and the combination of DWI and ADC images as inputs, the performance of DeepSym-3D-CNN is also investigated. Performance levels of all three models are evaluated by 5-fold cross-validation and the values of area under ROC curve (AUC) are compared by DeLong's test.

RESULTS

DeepSym-3D-CNN achieves an accuracy of 0.850 and an AUC of 0.864. DeLong's test of AUC values demonstrates that DeepSym-3D-CNN significantly outperforms other comparative models (p < 0.05). The highlighted regions in the feature maps of DeepSym-3D-CNN spatially match with AIS lesions. Meanwhile, DeepSym-3D-CNN using DWI images presents the significant higher AUC than that either using ADC images or using DWI-ADC images based on DeLong's test (p < 0.05).

CONCLUSIONS

DeepSym-3D-CNN is a potential method for automatically identifying AIS via DWI images and can be extended to other diseases with asymmetric lesions.

MRI characteristics in acute ischemic stroke patients with preceding direct oral anticoagulant therapy as compared to vitamin K antagonists

Background

Despite the utility of neuroimaging in the diagnostic and therapeutic management of patients with acute ischemic stroke (AIS), imaging characteristics in patients with preceding direct oral anticoagulants (DOAC) compared to vitamin K antagonists (VKA) have hardly been described. We aimed to determine presence of large vessel occlusion (LVO), thrombus length, infarction diameter, and occurrence of hemorrhagic transformation in AIS patients with preceding DOAC as compared to VKA therapy.

Methods

Using a prospectively collected cohort of AIS patients, we performed univariate and multivariable regression analyses regarding imaging outcomes. Additionally, we provide a sensitivity analysis for the subgroup of patients with confirmed therapeutic anticoagulation.

Results

We included AIS in patients with preceding DOAC (N = 75) and VKA (N = 61) therapy, median age 79 (IQR 70–83), 39% female. Presence of any LVO between DOAC and VKA patients (29.3% versus 37.7%, P = 0.361), and target LVO for endovascular therapy (26.7% versus 27.9%, P = 1.0) was equal with a similar occlusion pattern. DOAC as compared to VKA were associated with a similar rate of target LVO for EVT (aOR 0.835, 95% CI 0.368–1.898). The presence of multiple lesions and characteristics of the thrombus were similar in DOAC and VKA patients. Acute ischemic lesion diameter in real world patients was equal in patients taking DOAC as compared to VKA. Lesion diameter in VKA patients (median 13 mm, IQR 6–26 versus median 20 mm, IQR 7–36, P = 0.001), but not DOAC patients was smaller in the setting of confirmed therapeutic VKA. The frequency of radiological hemorrhagic transformation and symptomatic intracranial hemorrhage in OAC patients was low. Sensitivity analysis considering only patients with confirmed therapeutic anticoagulation did not change any of the results.

Conclusion

Preceding DOAC treatment showed equal rates of LVO and infarct size as compared to VKA in AIS patients. This study adds to the knowledge of imaging findings in AIS patients with preceding anticoagulation.

Evaluation of pituitary structures and lesions with turbo spin-echo diffusion-weighted imaging

BACKGROUND AND PURPOSE

Turbo spin-echo diffusion-weighted imaging (TSE-DWI) has not been used for evaluating pituitary lesions. We compared the usefulness of TSE-DWI and echo-planar (EP)-DWI for assessing normal pituitary structures and lesions.

MATERIALS AND METHODS

Our study included 41 consecutive patients (27 pituitary adenomas, 8 Rathke's cleft cysts, 4 craniopharyngiomas, 1 germinoma, 1 pituitary metastasis) who underwent conventional pre- and post-contrast magnetic resonance imaging (MRI) and TSE- and EP-DWI at 3T. Two observers independently performed qualitative assessment of normal pituitary structures and lesions on sagittal DWI and apparent diffusion coefficient (ADC) maps. One observer recorded ADC values of normal brain structures and pituitary lesions. Kappa (κ) statistics, Wilcoxon signed-rank test, intraclass correlation coefficient, Bland-Altman analysis, Pearson correlation coefficient and independent t-test were used for statistical analysis.

RESULTS

Interobserver agreement for qualitative evaluations was good to excellent (κ = 0.65-1.0). On both DWI and ADC maps, visualization of the pituitary gland, of the spatial relationship between the lesion and its normal surroundings, and the whole image quality were significantly better on TSE- than EP sequences (p < .01). In normal brain structures, the ADC value on TSE- and EP-sequences was significantly correlated (r = 0.6979, p < .05). The TSE-ADC value was significantly lower for pituitary adenomas than craniopharyngiomas (p < .05).

CONCLUSIONS

For the evaluation of normal pituitary structures and lesions, TSE-DWI is more useful than EP-DWI. The TSE-ADC value may help to differentiate between pituitary adenoma and craniopharyngioma.

Statistical properties of cerebral CT perfusion imaging systems. Part I. Cerebral blood volume maps generated from nondeconvolution-based systems

PURPOSE

The development and clinical employment of a computed tomography (CT) imaging system benefit from a thorough understanding of the statistical properties of the output images; cerebral CT perfusion (CTP) imaging system is no exception. A series of articles will present statistical properties of CTP systems and the dependence of these properties on system parameters. This Part I paper focuses on the signal and noise properties of cerebral blood volume (CBV) maps calculated using a nondeconvolution-based method.

METHODS

The CBV imaging chain was decomposed into a cascade of subimaging stages, which facilitated the derivation of analytical models for the probability density function, mean value, and noise variance of CBV. These models directly take CTP source image acquisition, reconstruction, and postprocessing parameters as inputs. Both numerical simulations and in vivo canine experiments were performed to validate these models.

RESULTS

The noise variance of CBV is linearly related to the noise variance of source images and is strongly influenced by the noise variance of the baseline images. Uniformly partitioning the total radiation dose budget across all time frames was found to be suboptimal, and an optimal dose partition method was derived to minimize CBV noise. Results of the numerical simulation and animal studies validated the derived statistical properties of CBV.

CONCLUSIONS

The statistical properties of CBV imaging systems can be accurately modeled by extending the linear CT systems theory. Based on the statistical model, several key signal and noise characteristics of CBV were identified and an optimal dose partition method was developed to improve the image quality of CBV.

Variability of optic nerve sheath diameter in acute ischemic stroke

Background:

Stroke is the third leading cause of death and the first cause of disability in the world. It holds an important place in hospital admissions and health expenses in the industrialized world.

Objective:

The aim of the study was to evaluate the relationship between optic nerve sheath diameter and the findings of brain computerized tomography scans and brain diffusion-weighted imaging and investigate the variability of optic nerve sheath diameter measured by ultrasonography in acute ischemic stroke.

Methods:

Patients who had acute ischemic stroke were included in Group A. Healthy adults were included in Group B as the control group. In addition, according to computerized tomography scans and diffusion-weighted imaging findings, Group A was divided into three subgroups. Patients with normal computerized tomography and diffusion-weighted imaging were included in Group 1, patients with normal computerized tomography and ischemic area on diffusion-weighted imaging were included in Group 2, and patients with ischemic area on computerized tomography and diffusion-weighted imaging were included in Group 3.

Results:

A total of 100 patients were included in Group A and 100 healthy adults included in Group B. The optic nerve sheath diameter values of Groups A and B were 5.4 ± 0.6 and 4.2 ± 0.4 mm (p < 0.001), respectively. The optic nerve sheath diameter cutoff value for detection of acute ischemic stroke was determined as 4.7 mm. The sensitivity and specificity at this cutoff value were determined as 89% and 90%, respectively. According to computerized tomography scans and diffusion-weighted imaging findings, there were 18 patients in Group 1, 56 patients in Group 2, and 26 patients in Group 3. Time from onset of symptoms to presentation to emergency department was shortest in Group 1 (3.0 ± 1.8 h). The widest optic nerve sheath diameter was calculated in Group 3 (optic nerve sheath diameter: 5.7 ± 0.6 mm).

Conclusion:

This study demonstrates that the optic nerve sheath diameter increases in acute ischemic stroke and it increases earlier than computerized tomography and diffusion-weighted imaging alteration occur. Therefore, optic nerve sheath diameter can be applied to assist the diagnosis of acute ischemic stroke with other imaging techniques with equivocal/negative results and determination of appropriate treatment, especially in cases with normal computerized tomography scan and diffusion-weighted imaging.

Application of Machine Learning to Automated Analysis of Cerebral Edema in Large Cohorts of Ischemic Stroke Patients

Cerebral edema contributes to neurological deterioration and death after hemispheric stroke but there remains no effective means of preventing or accurately predicting its occurrence. Big data approaches may provide insights into the biologic variability and genetic contributions to severity and time course of cerebral edema. These methods require quantitative analyses of edema severity across large cohorts of stroke patients. We have proposed that changes in cerebrospinal fluid (CSF) volume over time may represent a sensitive and dynamic marker of edema progression that can be measured from routinely available CT scans. To facilitate and scale up such approaches we have created a machine learning algorithm capable of segmenting and measuring CSF volume from serial CT scans of stroke patients. We now present results of our preliminary processing pipeline that was able to efficiently extract CSF volumetrics from an initial cohort of 155 subjects enrolled in a prospective longitudinal stroke study. We demonstrate a high degree of reproducibility in total cranial volume registration between scans (R = 0.982) as well as a strong correlation of baseline CSF volume and patient age (as a surrogate of brain atrophy, R = 0.725). Reduction in CSF volume from baseline to final CT was correlated with infarct volume (R = 0.715) and degree of midline shift (quadratic model, p < 2.2 × 10⁻¹⁶). We utilized generalized estimating equations (GEE) to model CSF volumes over time (using linear and quadratic terms), adjusting for age. This model demonstrated that CSF volume decreases over time (p < 2.2 × 10⁻¹³) and is lower in those with cerebral edema (p = 0.0004). We are now fully automating this pipeline to allow rapid analysis of even larger cohorts of stroke patients from multiple sites using an XNAT (eXtensible Neuroimaging Archive Toolkit) platform. Data on kinetics of edema across thousands of patients will facilitate precision approaches to prediction of malignant edema as well as modeling of variability and further understanding of genetic variants that influence edema severity.

Multi-delay ASL can identify leptomeningeal collateral perfusion in endovascular therapy of ischemic stroke

BACKGROUND AND PURPOSE

Multi-delay arterial spin-labeling (ASL) perfusion imaging has been used as a promising modality to evaluate cerebral perfusion. Our aim was to assess the association of leptomeningeal collateral perfusion scores based on ASL parameters with outcome of endovascular treatment in patients with acute ischemic stroke (AIS) in the middle cerebral artery (MCA) territory.

MATERIALS AND METHODS

ASL data at 4 post-labeling delay (PLD) times (PLD = 1.5, 2, 2.5, 3 s) were acquired during routine clinical magnetic resonance examination on AIS patients prior to endovascular treatment. A 3-point scale of leptomeningeal collateral perfusion grade on 10 anatomic regions was determined based on arterial transit times (ATT), cerebral blood flow (CBF), and arterial cerebral blood volume (CBV), estimated by the multi-delay ASL protocol. Based on a 90-day modified Rankin Scale (mRS), the patients were dichotomized to moderate/good (mRS 0-3) and poor outcome (mRS 4-6) and the regional collateral flow scores were compared.

RESULTS

Fifty-five AIS patients with unilateral MCA stroke (mean 73.95±14.82 years) including 23 males were enrolled. Compared with poor outcome patients, patients with moderate to good outcomes had a significantly higher leptomeningeal collateral perfusion scores on CBV (3.01±2.11 vs. 1.82±1.51, p=0.024) but no differences on scores on CBF (2.31±1.61 vs. 1.66±1.32, p=0.231) and ATT (2.67±2.33 vs. 3.42±3.37, p=0.593).

CONCLUSIONS

Higher leptomeningeal collateral perfusion scores on CBV images by ASL may be a specific marker of clinical outcome after endovascular treatment in patients with acute MCA ischemic stroke. Further study with larger sample size is warranted.

High-Performance Upconversion Nanoprobes for Multimodal MR Imaging of Acute Ischemic Stroke

Multimodal magnetic resonance (MR) imaging, including MR angiography (MRA) and MR perfusion (MRP), plays a critical role in the diagnosis and surveillance of acute ischemic stroke. However, these techniques are hindered by the low T1 relaxivity, short circulation time, and high leakage rate from vessels of clinical Magnevist. To address these problems, nontoxic polyethylene glycol (PEG)ylated upconversion nanoprobes (PEG-UCNPs) are synthesized and first adopted for excellent MRA and MRP imaging, featuring high diagnostic sensitivity toward acute ischemic stroke in high-resolution imaging. The investigations show that the agent possesses superior advantages over clinical Magnevist, such as much higher relaxivity, longer circulation time, and lower leakage rate, which guarantee much better imaging efficiency. Remarkably, an extremely small dosage (5 mg Gd kg(-1) ) of PEG-UCNPs provides high-resolution MRA imaging with the vascular system delineated much clearer than the Magnevist with clinical dosage as high as 108 mg Gd kg(-1) . On the other hand, the long circulation time of PEG-UCNPs enables the surveillance of the progression of ischemic stroke using MRA or MRP. Once translated, these PEG-UCNPs are expected to be a promising candidate for substituting the clinical Magnevist in MRA and MRP, which will significantly lengthen the imaging time window and improve the overall diagnostic efficiency.

Multimodal neuroimaging computing: the workflows, methods, and platforms

The last two decades have witnessed the explosive growth in the development and use of noninvasive neuroimaging technologies that advance the research on human brain under normal and pathological conditions. Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices. Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information. We review the current workflows and methods for multimodal neuroimaging computing, and also demonstrate how to conduct research using the established neuroimaging computing packages and platforms.

Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders

Multimodal neuroimaging is increasingly used in neuroscience research, as it overcomes the limitations of individual modalities. One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders. Multimodal neuroimaging computing enables the visualization and quantitative analysis of the alterations in brain structure and function, and has reshaped how neuroscience research is carried out. Research in this area is growing exponentially, and so it is an appropriate time to review the current and future development of this emerging area. Hence, in this paper, we review the recent advances in multimodal neuroimaging (MRI, PET) and electrophysiological (EEG, MEG) technologies, and their applications to the neuropsychiatric disorders. We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.

Impact of collaterals on successful revascularization in Solitaire FR with the intention for thrombectomy

BACKGROUND AND PURPOSE

Collaterals at angiography before endovascular therapy were analyzed to ascertain the effect on a novel end point of successful revascularization without symptomatic hemorrhage in the Solitaire FR With the Intention for Thrombectomy (SWIFT) study.

METHODS

Collateral grade (American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology) on baseline angiography was independently assessed, blind to other data, with statistical analyses delineating the relationship with clinical, laboratory, and imaging parameters.

RESULTS

Angiographic data on collaterals were available in 119 of 144 subjects (mean age, 67±12 years; 52% woman; median National Institutes of Health Stroke Scale, 18 [range, 8-28]). Worse collaterals were noted in subjects with elevated baseline blood glucose (P=0.013) and those with elevated baseline systolic blood pressure (P=0.039). Multivariate predictors of partial or worse collaterals included absence of prior hypertension (odds ratio, 4.049, P=0.012), smoking history (odds ratio, 3.822; P=0.013), and higher blood glucose (odds ratio, 1.017; P=0.022). Collaterals were strongly related to Alberta Stroke Program Early CT Score (ASPECTS) at baseline (0-1: median 8 [3-10]; 2-9 [5-10]; 3-9 [7-10]; 4-9 [8-10]; P<0.001) and 24 hours (0-1: median 1 [0-5]; 2-6 [0-10]; 3-8 [0-10]; 4-8 [4-8]; P<0.001). Better collaterals were linked with Thrombolysis in Cerebral Infarction 2b/3 reperfusion (P=0.019), better median National Institutes of Health Stroke Scale at day 7/discharge (P<0.001), and better day 90 modified Rankin Scale (P<0.001). Better collateral grade was associated with successful revascularization without symptomatic hemorrhage, mean 2.3 (95% confidence interval, 2.1-2.5) versus 1.9 (95% confidence interval, 1.7-2.2), P=0.021.

CONCLUSIONS

Better collaterals were associated with lower glucose, lower blood pressure, smaller baseline infarcts in SWIFT, and greater likelihood of successful revascularization without hemorrhage and good clinical outcomes.

CLINICAL TRIAL REGISTRATION URL

http://www.clinicaltrials.gov. Unique identifier: NCT01054560.