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Background and Purpose- Imaging is frequently used to select acute stroke patients for intra-arterial therapy. Quantitative cerebral blood flow can be measured noninvasively with arterial spin labeling magnetic resonance imaging. Cerebral blood flow levels in the contralateral (unaffected) hemisphere may affect capacity for collateral flow and patient outcome. The goal of this study was to determine whether higher contralateral cerebral blood flow (cCBF) in acute stroke identifies patients with better 90-day functional outcome. Methods- Patients were part of the prospective, multicenter iCAS study (Imaging Collaterals in Acute Stroke) between 2013 and 2017. Consecutive patients were enrolled after being diagnosed with anterior circulation acute ischemic stroke. Inclusion criteria were ischemic anterior circulation stroke, baseline National Institutes of Health Stroke Scale score ≥1, prestroke modified Rankin Scale score ≤2, onset-to-imaging time <24 hours, with imaging including diffusion-weighted imaging and arterial spin labeling. Patients were dichotomized into high and low cCBF groups based on median cCBF. Outcomes were assessed by day-1 and day-5 National Institutes of Health Stroke Scale; and day-30 and day-90 modified Rankin Scale. Multivariable logistic regression was used to test whether cCBF predicted good neurological outcome (modified Rankin Scale score, 0-2) at 90 days. Results- Seventy-seven patients (41 women) met the inclusion criteria with median (interquartile range) age of 66 (55-76) yrs, onset-to-imaging time of 4.8 (3.6-7.7) hours, and baseline National Institutes of Health Stroke Scale score of 13 (9-20). Median cCBF was 38.9 (31.2-44.5) mL per 100 g/min. Higher cCBF predicted good outcome at day 90 (odds ratio, 4.6 [95% CI, 1.4-14.7]; P=0.01), after controlling for baseline National Institutes of Health Stroke Scale, diffusion-weighted imaging lesion volume, and intra-arterial therapy. Conclusions- Higher quantitative cCBF at baseline is a significant predictor of good neurological outcome at day 90. cCBF levels may inform decisions regarding stroke triage, treatment of acute stroke, and general outcome prognosis. Clinical Trial Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT02225730.

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OBJECTIVES: To examine outcome of bilateral extracranial to intracranial (EC-IC) bypass surgeries for a Down syndrome patient with hard-to-treat epilepsy and moyamoya. MATERIALS AND METHODS: Superficial temporal arteries were anastamosed using an indirect bypass technique to middle cerebral arteries bilaterally to help limit perfusion deficits and seizure controls. RESULTS: Two superficial temporal to middle cerebral artery indirect bypass surgeries were performed within 3 months. Post-revascularization improvements included seizure control, gait, perfusion, wakefulness, language and quality of life. CONCLUSION: In patients with Down syndrome and moyamoya, improvements in seizure control and quality of life may occur with EC-IC bypass procedures.

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Appropriate management of adult gliomas requires an accurate histopathological diagnosis. However, the heterogeneity of gliomas can lead to misdiagnosis and undergrading, especially with biopsy. We evaluated the role of preoperative relative cerebral blood volume (rCBV) analysis in conjunction with histopathological analysis as a predictor of overall survival and risk of undergrading. We retrospectively identified 146 patients with newly diagnosed gliomas (WHO grade II-IV) that had undergone preoperative MRI with rCBV analysis. We compared overall survival by histopathologically determined WHO tumor grade and by rCBV using Kaplan-Meier survival curves and the Cox proportional hazards model. We also compared preoperative imaging findings and initial histopathological diagnosis in 13 patients who underwent biopsy followed by subsequent resection. Survival curves by WHO grade and rCBV tier similarly separated patients into low, intermediate, and high-risk groups with shorter survival corresponding to higher grade or rCBV tier. The hazard ratio for WHO grade III versus II was 3.91 (p = 0.018) and for grade IV versus II was 11.26 (p < 0.0001) and the hazard ratio for each increase in 1.0 rCBV units was 1.12 (p < 0.002). Additionally, 3 of 13 (23%) patients initially diagnosed by biopsy were upgraded on subsequent resection. Preoperative rCBV was elevated at least one standard deviation above the mean in the 3 upgraded patients, suggestive of undergrading, but not in the ten concordant diagnoses. In conclusion, rCBV can predict overall survival similarly to pathologically determined WHO grade in patients with gliomas. Discordant rCBV analysis and histopathology may help identify patients at higher risk for undergrading.

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OBJECTIVE Microcystic meningioma (MM) is a meningioma variant with a multicystic appearance that may mimic intrinsic primary brain tumors and other nonmeningiomatous tumor types. Dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI techniques provide imaging parameters that can differentiate these tumors according to hemodynamic and permeability characteristics with the potential to aid in preoperative identification of tumor type. METHODS The medical data of 18 patients with a histopathological diagnosis of MM were identified through a retrospective review of procedures performed between 2008 and 2012; DSC imaging data were available for 12 patients and DCE imaging data for 6. A subcohort of 12 patients with Grade I meningiomas (i.e., of meningoepithelial subtype) and 54 patients with Grade IV primary gliomas (i.e., astrocytomas) was also included, and all preoperative imaging sequences were analyzed. Clinical variables including patient sex, age, and surgical blood loss were also included in the analysis. Images were acquired at both 1.5 and 3.0 T. The DSC images were acquired at a temporal resolution of either 1500 msec (3.0 T) or 2000 msec (1.5 T). In all cases, parameters including normalized cerebral blood volume (CBV) and transfer coefficient (kTrans) were calculated with region-of-interest analysis of enhancing tumor volume. The normalized CBV and kTrans data from the patient groups were analyzed with 1-way ANOVA, and post hoc statistical comparisons among groups were conducted with the Bonferroni adjustment. RESULTS Preoperative DSC imaging indicated mean (± SD) normalized CBVs of 5.7 ± 2.2 ml for WHO Grade I meningiomas of the meningoepithelial subtype (n = 12), 4.8 ± 1.8 ml for Grade IV astrocytomas (n = 54), and 12.3 ± 3.8 ml for Grade I meningiomas of the MM subtype (n = 12). The normalized CBV measured within the enhancing portion of the tumor was significantly higher in the MM subtype than in typical meningiomas and Grade IV astrocytomas (p < 0.001 for both). Preoperative DCE imaging indicated mean kTrans values of 0.49 ± 0.20 min-1 in Grade I meningiomas of the meningoepithelial subtype (n = 12), 0.27 ± 0.12 min-1 for Grade IV astrocytomas (n = 54), and 1.35 ± 0.74 min-1 for Grade I meningiomas of the MM subtype (n = 6). The kTrans was significantly higher in the MM variants than in the corresponding nonmicrocystic Grade 1 meningiomas and Grade IV astrocytomas (p < 0.001 for both). Intraoperative blood loss tended to increase with increased normalized CBV (R = 0.45, p = 0.085). CONCLUSIONS An enhancing cystic lesion with a normalized CBV greater than 10.3 ml or a kTrans greater than 0.88 min-1 should prompt radiologists and surgeons to consider the diagnosis of MM rather than traditional Grade I meningioma or high-grade glioma in planning surgical care. Higher normalized CBVs tend to be associated with increased intraoperative blood loss.

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PURPOSE: To evaluate the clinical utility of fast whole-brain macromolecular proton fraction ( MPF macromolecular proton fraction ) mapping in multiple sclerosis ( MS multiple sclerosis ) and compare MPF macromolecular proton fraction with established quantitative magnetic resonance (MR) imaging measures of tissue damage including magnetization transfer ( MT magnetization transfer ) ratio and relaxation rate (R1). MATERIALS AND METHODS: In this institutional review board-approved and HIPAA-compliant study, 14 healthy control participants, 18 relapsing-remitting MS multiple sclerosis ( RRMS relaxing-remitting MS ) patients, and 12 secondary progressive MS multiple sclerosis ( SPMS secondary progressive MS ) patients provided written informed consent and underwent 3-T MR imaging. Three-dimensional MPF macromolecular proton fraction maps were reconstructed from MT magnetization transfer -weighted images and R1 maps by the single-point method. Mean MPF macromolecular proton fraction , R1, and MT magnetization transfer ratio in normal-appearing white matter ( WM white matter ), gray matter ( GM gray matter ), and lesions were compared between subject groups by using analysis of variance. Correlations (Pearson r) between imaging data and clinical scores (Expanded Disability Status Scale [EDSS] and MS multiple sclerosis Functional Composite [ MSFC MS functional composite ]) were compared by using Hotelling-Williams test. RESULTS: RRMS relaxing-remitting MS patients had lower WM white matter and GM gray matter MPF macromolecular proton fraction than controls, with percentage decreases of 6.5% (P < .005) and 5.4% (P < .05). MPF macromolecular proton fraction in SPMS secondary progressive MS was reduced relative to RRMS relaxing-remitting MS in WM white matter , GM gray matter , and lesions by 6.4% (P < .005), 13.4% (P < .005), and 11.7% (P < .05), respectively. EDSS Expanded Disability Status Scale and MSFC MS functional composite demonstrated strongest correlations with MPF macromolecular proton fraction in GM gray matter (r = -0.74 and 0.81; P < .001) followed by WM white matter (r = -0.57 and 0.72; P < .01) and lesions (r = -0.42 and 0.50; P < .05). R1 and MT magnetization transfer ratio in all tissues were significantly less correlated with clinical scores than GM gray matter MPF macromolecular proton fraction (P < .05). CONCLUSION: MPF macromolecular proton fraction mapping enables quantitative assessment of demyelination in normal-appearing brain tissues and shows primary clinical relevance of GM gray matter damage in MS multiple sclerosis . MPF macromolecular proton fraction outperforms MT magnetization transfer ratio and R1 in detection of MS multiple sclerosis -related tissue changes.

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BACKGROUND: Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice. OBJECTIVE: The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis. METHODS: CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers. EXPECTED OUTCOMES: CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps. DISCUSSION: CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.

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OBJECTIVES: One risk with placement of an epidural blood patch (EDBP) is spinal cord or nerve root compression resulting from the epidural blood volume injected, a complication necessitating immediate surgical decompression. We could not find a previous report of this in the literature. Here, we review and discuss one such case. CASE REPORT: A patient was treated with 2 EDBPs for a presumptive cerebrospinal fluid leak 3 weeks after an epidural steroid injection. The second EDBP was performed under direct fluoroscopic guidance, yet resulted in spinal cord compression with radiologic evidence of an epidural hematoma. The patient developed acute cauda equina syndrome and required an emergent decompressive laminectomy resulting in partial resolution of neurological symptoms. One year after the procedure, the patient has recovered most of her motor function but with some persistent numbness below the left knee and a left foot drop. CONCLUSIONS: A cauda equina syndrome from an epidural hematoma may occur as a rare complication of an EDBP, even with direct fluoroscopic guidance. Early diagnosis of symptoms and prompt surgical evacuation of an epidural hematoma is essential and may result in the resolution of symptoms. This complication remains a rare occurrence and should not deter the performance of an EDBP, when indicated.

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Glioblastoma Mulitforme is highly infiltrative, making precise delineation of tumor margin difficult. Multimodality or multi-parametric MR imaging sequences promise an advantage over anatomic sequences such as post contrast enhancement as methods for determining the spatial extent of tumor involvement. In considering multi-parametric imaging sequences however, manual image segmentation and classification is time-consuming and prone to error. As a preliminary step toward integration of multi-parametric imaging into clinical assessments of primary brain tumors, we propose a machine-learning based multi-parametric approach that uses radiologist generated labels to train a classifier that is able to classify tissue on a voxel-wise basis and automatically generate a tumor segmentation. A random forests classifier was trained using a leave-one-out experimental paradigm. A simple linear classifier was also trained for comparison. The random forests classifier accurately predicted radiologist generated segmentations and tumor extent.

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The clinical manifestations of intracranial tumors are usually referable to the anatomic area of the brain involved or adjacent structures. Some anatomic regions may allow a tumor to reach substantial size while remaining clinically silent. In contrast, small lesions in critical areas are more likely to present early. The initial diagnosis of intracranial tumors is most efficiently made by imaging. This article discusses the clinicoanatomic features and imaging characteristics of brain tumors, including the use of dynamic susceptibility-weighted, T1 dynamic, diffusion, functional, and diffusion tensor imaging.

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The human insular cortex, or the lobus insularis, is considered the developmentally most primitive lobe of the telencephalon. Covered by an overlying cortical lid, the insula has functions that are distinct from yet related to those of the adjacent temporal lobe and deep limbic structures. In the first part of this paper the authors outline the development of the human insula, including the cellular heterogeneity comprising the various parts of the insular lobe. Using the understanding gained from the development of the insula they then address implications of insular development for cortical development and connection as well as for tumorigenesis and tumor spread from the insula to other cortical structures, most notably the temporal lobe. An understanding of cortico-insular development and interconnection allows for both a better understanding of insular pathology and also facilitates planning of resection of cortico-insular gliomas to avoid damage to eloquent structures.

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PURPOSE OF REVIEW: Imaging is a critical component of both neuroendocrine lesion identification and anatomic delineation for treatment planning. Cross-sectional and isotopic-based physiologic imaging techniques have, to date, been the radiological modalities of choice. This review focuses on recent advances in imaging that are related to the evaluation of neuroendocrine abnormalities, in particular advances in MRI. RECENT FINDINGS: Magnetic-resonance perfusion examination of tissue characteristics in the pituitary, adrenal and thyroid glands indicates that, in many cases, adenomas of these glands have distinguishable hemodynamic characteristics relative to the parenchyma of the gland as a whole and to other lesions. Moreover, perfusion metrics might provide a basis for evaluating response to therapy (in the pituitary) and delineation of lesions in the adrenal and thyroid glands. Anisotropy-based imaging techniques show promise in providing direct, relevant information about pituitary tumor involvement of the adjacent cavernous sinuses. SUMMARY: The most recent methodological advances in the imaging of neuroendocrine disorder involves the continued development and application of MRI, in particular using pulse sequences, which provide a greater insight into the internal structure and physiology of the tissues interrogated, relative to standard sequences.

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The application of functional magnetic resonance imaging (fMRI) to elucidation of seizures and epilepsy has been built primarily upon a framework derived from cortical responses to periodic sensory (and cognitive) stimuli. This analytical approach relies upon assumptions that may be less applicable to the problem of seizure origination. Because of the heterogeneous and complex nature of seizures, a number of quantitative methodologies have been derived to understand fMRI changes that are associated with epileptiform neural activity. Separated broadly, these can be divided into those making some set of assumptions about the form of the MRI signal response to neural activation (the general linear model), and those that are data driven. It is likely that a combination of methodologies, where data driven methods are "informed" by knowledge of the underlying neurobiological process will provide the greatest insight into the underlying neurobiological basis of seizure origination.

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