Diffusion-Weighted Imaging Fluid-Attenuated Inversion Recovery Mismatch on Portable, Low-Field Magnetic Resonance Imaging Among Acute Stroke Patients.

OBJECTIVE: For stroke patients with unknown time of onset, mismatch between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can guide thrombolytic intervention. However, access to MRI for hyperacute stroke is limited. Here, we sought to evaluate whether a portable, low-field (LF)-MRI scanner can identify DWI-FLAIR mismatch in acute ischemic stroke. METHODS: Eligible patients with a diagnosis of acute ischemic stroke underwent LF-MRI acquisition on a 0.064-T scanner within 24 h of last known well. Qualitative and quantitative metrics were evaluated. Two trained assessors determined the visibility of stroke lesions on LF-FLAIR. An image coregistration pipeline was developed, and the LF-FLAIR signal intensity ratio (SIR) was derived. RESULTS: The study included 71 patients aged 71 ± 14 years and a National Institutes of Health Stroke Scale of 6 (interquartile range 3-14). The interobserver agreement for identifying visible FLAIR hyperintensities was high (κ = 0.85, 95% CI 0.70-0.99). Visual DWI-FLAIR mismatch had a 60% sensitivity and 82% specificity for stroke patients <4.5 h, with a negative predictive value of 93%. LF-FLAIR SIR had a mean value of 1.18 ± 0.18 <4.5 h, 1.24 ± 0.39 4.5-6 h, and 1.40 ± 0.23 >6 h of stroke onset. The optimal cut-point for LF-FLAIR SIR was 1.15, with 85% sensitivity and 70% specificity. A cut-point of 6.6 h was established for a FLAIR SIR <1.15, with an 89% sensitivity and 62% specificity. INTERPRETATION: A 0.064-T portable LF-MRI can identify DWI-FLAIR mismatch among patients with acute ischemic stroke. Future research is needed to prospectively validate thresholds and evaluate a role of LF-MRI in guiding thrombolysis among stroke patients with uncertain time of onset. ANN NEUROL 2024.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Superior cortical venous anatomy for endovascular device implantation: a systematic review.

Endovascular electrode arrays provide a minimally invasive approach to access intracranial structures for neural recording and stimulation. These arrays are currently used as brain-computer interfaces (BCIs) and are deployed within the superior sagittal sinus (SSS), although cortical vein implantation could improve the quality and quantity of recorded signals. However, the anatomy of the superior cortical veins is heterogenous and poorly characterised. MEDLINE and Embase databases were systematically searched from inception to December 15, 2023 for studies describing the anatomy of the superior cortical veins. A total of 28 studies were included: 19 cross-sectional imaging studies, six cadaveric studies, one intraoperative anatomical study and one review. There was substantial variability in cortical vein diameter, length, confluence angle, and location relative to the underlying cortex. The mean number of SSS branches ranged from 11 to 45. The vein of Trolard was most often reported as the largest superior cortical vein, with a mean diameter ranging from 2.1 mm to 3.3 mm. The mean vein of Trolard was identified posterior to the central sulcus. One study found a significant age-related variability in cortical vein diameter and another identified myoendothelial sphincters at the base of the cortical veins. Cortical vein anatomical data are limited and inconsistent. The vein of Trolard is the largest tributary vein of the SSS; however, its relation to the underlying cortex is variable. Variability in cortical vein anatomy may necessitate individualized pre-procedural planning of training and neural decoding in endovascular BCI. Future focus on the relation to the underlying cortex, sulcal vessels, and vessel wall anatomy is required.

Fluid suppression in amide proton transfer-weighted (APTw) CEST imaging: New theoretical insights and clinical benefits.

PURPOSE: Amide proton transfer-weighted (APTw) MRI at 3T provides a unique contrast for brain tumor imaging. However, APTw imaging suffers from hyperintensities in liquid compartments such as cystic or necrotic structures and provides a distorted APTw signal intensity. Recently, it has been shown that heuristically motivated fluid suppression can remove such artifacts and significantly improve the readability of APTw imaging. THEORY AND METHODS: In this work, we show that the fluid suppression can actually be understood by the known concept of spillover dilution, which itself can be derived from the Bloch-McConnell equations in comparison to the heuristic approach. Therefore, we derive a novel post-processing formula that efficiently removes fluid artifact, and explains previous approaches. We demonstrate the utility of this APTw assessment in silico, in vitro, and in vivo in brain tumor patients acquired at MR scanners from different vendors. RESULTS: Our results show a reduction of the CEST signals from fluid environments while keeping the APTw-CEST signal intensity almost unchanged for semi-solid tissue structures such as the contralateral normal appearing white matter. This further allows us to use the same color bar settings as for conventional APTw imaging. CONCLUSION: Fluid suppression has considerable value in improving the readability of APTw maps in the neuro-oncological field. In this work, we derive a novel post-processing formula from the underlying Bloch-McConnell equations that efficiently removes fluid artifact, and explains previous approaches which justify the derivation of this metric from a theoretical point of view, to reassure the scientific and medical field about its use.

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the cavernous carotid region. The authors evaluated a deep learning pipeline for segmentation of vessels and IAs from CTA using coregistered, segmented DSA images as ground truth. METHODS: Using 50 paired CTA-DSA images, the authors trained (n = 27), validated (n = 3), and tested (n = 20) a deep learning model (3D DeepMedic) for cerebrovasculature segmentation from CTA. A landmark-based coregistration algorithm was used for registration and upsampling of CTA images to paired DSA images. Segmented vessels from the DSA were used as the ground truth. Accuracy of the model for vessel segmentation was evaluated using conventional metrics (dice similarity coefficient [DSC]) and vessel segmentation-specific metrics, like connectivity-area-length (CAL). On the test cases (20 IAs), 3 expert raters attempted to detect and segment IAs. For each rater, the authors recorded the rate of IA detection, and for detected IAs, raters segmented and calculated important IA morphology parameters to quantify the differences in IA segmentation by raters to segmentations by DeepMedic. The agreement between raters, DeepMedic, and ground truth was assessed using Krippendorf's alpha. RESULTS: In testing, the DeepMedic model yielded a CAL of 0.971 ± 0.007 and a DSC of 0.868 ± 0.008. The model prediction delineated all IAs and resulted in average error rates of < 10% for all IA morphometrics. Conversely, average IA detection accuracy by the raters was 0.653 (undetected IAs were present to a significantly greater degree on the ICA, likely due to those in the cavernous region, and were significantly smaller). Error rates for IA morphometrics in rater-segmented cases were significantly higher than in DeepMedic-segmented cases, particularly for neck (p = 0.003) and surface area (p = 0.04). For IA morphology, agreement between the raters was acceptable for most metrics, except for the undulation index (α = 0.36) and the nonsphericity index (α = 0.69). Agreement between DeepMedic and ground truth was consistently higher compared with that between expert raters and ground truth. CONCLUSIONS: This CTA segmentation network (DeepMedic trained on DSA-segmented vessels) provides a high-fidelity solution for CTA vessel segmentation, particularly for vessels and IAs in the carotid cavernous region.

The Right Imaging Protocol for the Right Patient.

OBJECTIVE: This article provides a high-level overview of the challenge of choosing the right imaging approach for an individual patient. It also presents a generalizable approach that can be applied to practice regardless of specific imaging technologies. ESSENTIAL POINTS: This article constitutes an introduction to the in-depth, topic-focused analyses in the rest of this issue. It examines the broad principles that guide placing a patient on the right diagnostic trajectory, illustrated with real-life examples of current protocol recommendations and cases of advanced imaging techniques, as well as some thought experiments. Thinking about diagnostic imaging strictly in terms of imaging protocols is often inefficient because these protocols can be vague and have numerous variations. Broadly defined protocols may be sufficient, but their successful use often depends largely on the particular circumstances, with special emphasis on the relationship between neurologists and radiologists.

Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging.

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Prognosis of ischemia recurrence in patients with moderate intracranial atherosclerotic disease using quantitative MRA measurements.

Purpose: To investigate the relation between delayed ischemic stroke and the intracranial atherosclerotic disease (ICAD) hemodynamics as determined by Non-invasive Optimal Vessel Analysis (NOVA) MRI measurements. Materials and Methods: Thirty-three patients with ICAD were enrolled in this study. All patients underwent clinically indicated angioplasty followed by 2-dimensional phase contrast MR (2D PCMR) performed on a 3.0 Tesla MRI scanner using either a 16-channel neurovascular coil or 32-channel head coil. The volumetric flow rate measurements were calculated from 2D PCMR with Non-invasive Optimal Vessel Analysis (NOVA) software (VasSol, Chicago, IL, USA). Flow rate measurements were obtained in 20 major arteries distal, proximal and within the Circle of Willis. Patients were followed up for six month, and ischemia reoccurrence and location were recorded. Receiver operating characteristic (ROC) analysis was performed using flow rates measurements in the ipsilateral side of the ischemic event occurrence. Results: Complete set of measurements was achieved in n=34. Left and right hemisphere ischemia recurrence was observed in seven and three cases respectively. Best predictor of ischemic event reoccurrence was flow rate in the middle cerebral artery with area under the ROC of 0.821±0.109. Conclusions: This is an effectiveness study to determine whether blood flow measurements in the intracranial vasculature may be predictive of future ischemic events. Our results demonstrated significant correlation between the blood flow measurements using 2D PCMR processed with the NOVA software and the reoccurrence of ischemia. These results support further investigation for using this method for risk stratification of ICAD patients.

A Beginner's Guide to Arterial Spin Labeling (ASL) Image Processing.

Arterial spin labeling (ASL) is a non-invasive and cost-effective MRI technique for brain perfusion measurements. While it has developed into a robust technique for scientific and clinical use, its image processing can still be daunting. The 2019 Ann Arbor ISMRM ASL working group established that education is one of the main areas that can accelerate the use of ASL in research and clinical practice. Specifically, the post-acquisition processing of ASL images and their preparation for region-of-interest or voxel-wise statistical analyses is a topic that has not yet received much educational attention. This educational review is aimed at those with an interest in ASL image processing and analysis. We provide summaries of all typical ASL processing steps on both single-subject and group levels. The readers are assumed to have a basic understanding of cerebral perfusion (patho) physiology; a basic level of programming or image analysis is not required. Starting with an introduction of the physiology and MRI technique behind ASL, and how they interact with the image processing, we present an overview of processing pipelines and explain the specific ASL processing steps. Example video and image illustrations of ASL studies of different cases, as well as model calculations, help the reader develop an understanding of which processing steps to check for their own analyses. Some of the educational content can be extrapolated to the processing of other MRI data. We anticipate that this educational review will help accelerate the application of ASL MRI for clinical brain research.

Automated Cerebral Vessel Segmentation of Magnetic Resonance Imaging in Patients with Intracranial Atherosclerotic Diseases.

Time-of-flight (TOF) magnetic resonance angiography is a non-invasive imaging modality for the diagnosis of intracranial atherosclerotic diseases (ICAD). Evaluation of the degree of the stenosis and status of posterior and anterior communicating arteries to supply enough blood flow to the distal arteries is very critical, which requires accurate evaluation of arteries. Recently, deep-learning methods have been firmly established as a robust tool in medical image segmentation, which has been resulted in developing multiple customized algorithms. For instance, BRAVE-NET, a context-based successor of U-Net-has shown promising results in MRA cerebrovascular segmentation. Another widely used context-based 3D CNN-DeepMedic-has been shown to outperform U-Net in cerebrovascular segmentation of 3D digital subtraction angiography. In this study, we aim to train and compare the two state-of-the-art deep-learning networks, BRAVE-NET and DeepMedic, for automated and reliable brain vessel segmentation from TOF-MRA images in ICAD patients. Using specially labeled data-labeled on TOF MRA and corrected on high-resolution black-blood MRI, of 51 patients with ICAD due to severe stenosis, we trained and tested both models. On an independent test dataset of 11 cases, DeepMedic slightly outperformed BRAVE-NET in terms of DSC (0.905±0.012 vs 0.893±0.015, p: 0.539) and 95HD (0.754±0.223 vs 1.768±0.609, p: 0.134), and significantly outperformed BRAVE-NET in terms of Recall (0.940±0.023 vs 0.855±0.030, p: 0.036). Qualitative assessment confirmed the superiority of DeepMedic in capturing the small and distal arteries. While BRAVE-NET consistently reported higher precision, DeepMedic generally overpredicted and could better visualize the smaller and distal arteries. In future studies, ensemble models that can leverage best of both should be developed and tested on larger datasets.Clinical Relevance- This study helps elevate the state-of-the-art for brain vessel segmentation from non-invasive MRA, which could accelerate the translation of vessel status-based biomarkers into the clinical setting.

Aneurysm risk metrics and hemodynamics are associated with greater vessel wall enhancement in intracranial aneurysms.

Vessel wall enhancement (VWE) in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for intracranial aneurysm (IA) risk stratification. In this study, we investigated the relationship between VWE features, risk metrics, morphology and hemodynamics in 41 unruptured aneurysms. We reconstructed the IA geometries from MR angiography and mapped pituitary stalk-normalized MRI intensity on the aneurysm surface using an in-house tool. For each case, we calculated the maximum intensity (CRstalk) and IA risk (via size and the rupture resemblance score (RRS)). We performed correlation analysis to assess relationships between CRstalk and IA risk metrics (size and RRS), as well as each parameter encompassed in RRS, i.e. aneurysmal size ratio (SR), normalized wall shear stress (WSS) and oscillatory shear index. We found that CRstalk had a strong correlation (Pearson correlation coefficient, PCC = 0.630) with size and a moderate correlation (PCC = 0.472) with RRS, indicating an association between VWE and IA risk. Furthermore, CRstalk had a weak negative correlation with normalized WSS (PCC = -0.320) and a weak positive correlation with SR (PCC = 0.390). Local voxel-based analysis showed only a weak negative correlation between normalized WSS and contrast-enhanced MRI signal intensity (PCC = -0.240), suggesting that if low-normalized WSS induces enhancement-associated pathobiology, the effect is not localized.

An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms.

BACKGROUND: VWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a tool for the visualization, quantification and objective identification of regions with VWE. METHODS: N = 41 3D T1-MRI and 3D TOF-MRA IA images from 38 patients were obtained and co-registered. A contrast-enhanced MRI was normalized by the enhancement intensity of the pituitary stalk and signal intensities were mapped onto the surface of IA models generated from segmented MRA. N = 30 IAs were used to identify the optimal signal intensity value to distinguish the enhancing and non-enhancing regions (marked by an experienced neuroradiologist). The remaining IAs (n = 11) were used to validate the threshold. We tested if the enhancement area ratio (EAR-ratio of the enhancing area to the IA surface-area) could identify high risk aneurysms as identified by the ISUIA clinical score. RESULTS: A normalized intensity of 0.276 was the optimal threshold to delineate enhancing regions, with a validation accuracy of 81.7%. In comparing the overlap between the identified enhancement regions against those marked by the neuroradiologist, our method had a dice coefficient of 71.1%. An EAR of 23% was able to discriminate high-risk cases with an AUC of 0.7. CONCLUSIONS: We developed and validated a pipeline for the visualization and objective identification of VWE regions that could potentially help evaluation of IAs become more reliable and consistent.

Neuroimaging for the Neurologist: Clinical MRI and Future Trends.

MRI is a commonly used diagnostic tool in neurology, and all neurologists should possess a working knowledge of imaging fundamentals. An overview of current and impending MRI techniques is presented to help the referring clinician communicate better with the imaging department, understand the utility and limitations of current and emerging technology, improve specificity and appropriateness when ordering MRI studies, and recognize key findings.

Characteristics of Tremor Induced by Lesions of the Cerebellum.

It is a clinical experience that acute lesions of the cerebellum induce pathological tremor, which tends to improve. However, quantitative characteristics, imaging correlates, and recovery of cerebellar tremor have not been systematically investigated. We studied the prevalence, quantitative parameters measured with biaxial accelerometry, and recovery of pathological tremor in 68 patients with lesions affecting the cerebellum. We also investigated the correlation between the occurrence and characteristics of tremor and lesion localization using 3D T1-weighted MRI images which were normalized and segmented according to a spatially unbiased atlas template for the cerebellum. Visual assessment detected pathological tremor in 19% while accelerometry in 47% of the patients. Tremor was present both in postural and intentional positions, but never at rest. Two types of pathological tremor were distinguished: (1) low-frequency tremor in 36.76% of patients (center frequency 2.66 ± 1.17 Hz) and (2) normal frequency-high-intensity tremor in 10.29% (center frequency 8.79 ± 1.43 Hz). The size of the lesion did not correlate with the presence or severity of tremor. Involvement of the anterior lobe and lobule VI was related to high tremor intensity. In all followed up patients with acute cerebellar ischemia, the tremor completely recovered within 8 weeks. Our results indicate that cerebellar lesions might induce pathological postural and intentional tremor of 2-3 Hz frequency. Due to its low frequency and low amplitude, quantitative tremorometry is neccessary to properly identify it. There is no tight correlation between lesion localization and quantitative characteristics of cerebellar tremor.

Potential Safety Issues Related to the Use of Gadolinium-based Contrast Agents.

PURPOSE OF REVIEW: This article reviews recent research on gadolinium deposit formation in the brain linked to contrast-enhanced MRI studies. RECENT FINDINGS: Human and animal studies have confirmed the presence of gadolinium in the brain following the serial administration of gadolinium-based contrast agents. This is a relatively new and growing field of research primarily driven by concerns regarding unknown and potentially harmful side effects of gadolinium-based contrast agents. Retrospective observational in vivo studies in humans demonstrated T1 shortening effects in the brain parenchyma resulting from gadolinium exposure. These studies were followed by postmortem human and animal studies. Evidence exists that gadolinium may cause deposits in the brain and that this may occur independently of impaired renal function and in the presence of an intact blood-brain barrier. Gadolinium deposition has been linked primarily with the use of linear, rather than macrocyclic, gadolinium-based contrast agents. SUMMARY: The formation of gadolinium deposits and its implications have been the focus of only a small number of research groups. The currently available data must be verified, and the potential factors that may be linked to this phenomenon and the clinical significance must be explored. Depending on future findings, changes in the clinical application of gadolinium-based contrast agents may be expected.

Neuroimaging of spine tumors.

Intramedullary, intradural/extramedullary, and extradural spine tumors comprise a wide range of neoplasms with an even wider range of clinical symptoms and prognostic features. Magnetic resonance imaging (MRI), commonly used to evaluate the spine in patients presenting with pain, can further characterize lesions that may be encountered on other imaging studies, such as bone scintigraphy or computed tomography (CT). The advantage of the MRI is its multiplane capabilities, superior contrast agent resolution, and flexible protocols that play an important role in assessing tumor location, extent in directing biopsy, in planning proper therapy, and in evaluating therapeutic results. A multimodality approach can be used to fully characterize the lesion and the combination of information obtained from the different modalities usually narrows the diagnostic possibilities significantly. The diagnosis of spinal tumors is based on patient age, topographic features of the tumor, and lesion pattern, as seen at CT and MRI. The shift to high-end imaging incorporating diffusion-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy, whole-body short tau inversion recovery, positron emission tomography, intraoperative and high-field MRI as part of the mainstream clinical imaging protocol has provided neurologists, neuro-oncologists, and neurosurgeons a window of opportunity to assess the biologic behavior of spine neoplasms. This chapter reviews neuroimaging of spine tumors, primary and secondary, discussing routine and newer modalities that can reduce the significant morbidity associated with these neoplasms.

Basilar Invagination, Basilar Impression, and Platybasia: Clinical and Imaging Aspects.

The congenital and acquired deformities of the craniovertebral junction (CVJ), such as basilar invagination, basilar impression, or platybasia, can present in the form of slowly progressive or acute neurologic deterioration. In many cases, an insidious headache is the only symptom and can be a diagnostic challenge for the neurologist. Proper imaging studies as well as recognizing often associated neurologic or systemic conditions are required for early diagnosis and effective therapy. In the current report, the primary focus will be on clinical aspects of these CVJ abnormalities; the pathologic and radiologic aspects, such as developmental and pathophysiologic background or radiographic analysis, will be discussed briefly, confined to clinically relevant data.

Selegiline promotes NOTCH-JAGGED signaling in astrocytes of the peri-infarct region and improves the functional integrity of the neurovascular unit in a rat model of focal ischemia.

PURPOSE: Our experiments aimed at exploring potential neurorestorative mechanisms of selegiline, a compound routinely used in the treatment of Parkinson's disease and previously shown to improve the functional recovery of stroke patients. METHODS: Selegiline was administered continuously via osmotic mini-pumps between 48 and 216 hours following middle cerebral artery occlusion (MCAO) in rats. Twenty-four hours before sacrifice, the animals underwent magnetic resonance imaging (MRI). After decapitation, the peri-infarct region was dissected to perform a TAQMAN array gene expression study, and brains were fixed for immunolabeling. RESULTS: In addition to the previously known induction of anti-apoptosis genes, selegiline significantly increased the mRNA level of Notch 1 receptor and its ligand Jagged 1. Immunohistochemistry demonstrated elevated Notch 1 and Jagged 1 immunoreactivities in the peri-infarct region. Double labeling with glial markers revealed that both Notch 1 and Jagged 1 were expressed in astrocytes but not in microglia. MRI examination indicated significantly reduced edema in selegiline-treated rats compared to control MCAO rats, and increased capillary network density was found in the peri-infarct region of the selegiline-treated animals. CONCLUSION: Our results suggest that selegiline treatment enhances Notch-Jagged signaling in astrocytes, reduces peri-lesional edema and potentially helps preserve the capillary network following focal ischemia.