Capillary Hemangioma of the Spinal Cord: Case Report and Systematic Review of Literature.

BACKGROUND: Capillary hemangiomas are rare vascular lesions that rarely affect the central nervous system. When they present within the spinal canal, they are typically confined intradurally, with intramedullary extension rare. We present a rare case of spinal intramedullary capillary hemangioma, with a systematic review of the literature. METHODS: Medical records and imaging data were retrospectively reviewed using the health record software EPIC (Verona, Wisconsin, USA) and the radiology management software system RIS/PACS (Radiology Information System/Picture Archiving and Communication System; QREADS). The report was written in accordance with the CARE (case reports) guidelines. We also performed a systematic review of the literature on all cases of intramedullary spinal capillary hemangiomas in accordance with PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. RESULTS: We report a case of a 54-year-old man who presented with progressive paraplegia and sensory deficits in the lower extremities. Spinal magnetic resonance imaging showed an intramedullary enhancing lesion centered at T11 with associated spinal cord compression. He underwent thoracic laminectomy and gross total resection of the lesion without complications and subsequent improvement on his neurological examination. Histological examination showed findings consistent with a capillary hemangioma. The literature review also documented 21 studies with a combined total of 38 cases of intramedullary spinal capillary hemangioma. CONCLUSIONS: Purely intramedullary capillary hemangiomas are unusual spinal lesions with only a few cases reported in the literature. These should be considered in the differential diagnosis of intramedullary tumors. Surgical management remains the first line of treatment for symptomatic patients.

MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma.

PURPOSE: Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients. METHODS: 21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin. RESULTS: Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor's enhancing zone and necrotic core and the L-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5). CONCLUSIONS: This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

A multivariate metabolic imaging marker for behavioral variant frontotemporal dementia.

INTRODUCTION: The heterogeneity of behavioral variant frontotemporal dementia (bvFTD) calls for multivariate imaging biomarkers. METHODS: We studied a total of 148 dementia patients from the Feinstein Institute (Center-A: 25 bvFTD and 10 Alzheimer's disease), Technical University of Munich (Center-B: 44 bvFTD and 29 FTD language variants), and Alzheimer's Disease Neuroimaging Initiative (40 Alzheimer's disease subjects). To identify the covariance pattern of bvFTD (behavioral variant frontotemporal dementia-related pattern [bFDRP]), we applied principal component analysis to combined 18F-fluorodeoxyglucose-positron emission tomography scans from bvFTD and healthy subjects. The phenotypic specificity and clinical correlates of bFDRP expression were assessed in independent testing sets. RESULTS: The bFDRP was identified in Center-A data (24.1% of subject × voxel variance; P < .001), reproduced in Center-B data (P < .001), and independently validated using combined testing data (receiver operating characteristics-area under the curve = 0.97; P < .0001). The expression of bFDRP was specifically elevated in bvFTD patients (P < .001) and was significantly higher at more advanced disease stages (P = .035:duration; P < .01:severity). DISCUSSION: The bFDRP can be used as a quantitative imaging marker to gauge the underlying disease process and aid in the differential diagnosis of bvFTD.

Increased putamen hypercapnic vasoreactivity in levodopa-induced dyskinesia.

In a rodent model of Parkinson's disease (PD), levodopa-induced involuntary movements have been linked to striatal angiogenesis - a process that is difficult to document in living human subjects. Angiogenesis can be accompanied by localized increases in cerebral blood flow (CBF) responses to hypercapnia. We therefore explored the possibility that, in the absence of levodopa, local hypercapnic CBF responses are abnormally increased in PD patients with levodopa-induced dyskinesias (LID) but not in their nondyskinetic (NLID) counterparts. We used H215O PET to scan 24 unmedicated PD subjects (12 LID and 12 NLID) and 12 matched healthy subjects in the rest state under normocapnic and hypercapnic conditions. Hypercapnic CBF responses were compared to corresponding levodopa responses from the same subjects. Group differences in hypercapnic vasoreactivity were significant only in the posterior putamen, with greater CBF responses in LID subjects compared with the other subjects. Hypercapnic and levodopa-mediated CBF responses measured in this region exhibited distinct associations with disease severity: the former correlated with off-state motor disability ratings but not symptom duration, whereas the latter correlated with symptom duration but not motor disability. These are the first in vivo human findings linking LID to microvascular changes in the basal ganglia.

Distinct brain networks underlie cognitive dysfunction in Parkinson and Alzheimer diseases.

OBJECTIVE: To determine whether cognitive impairment in Parkinson disease (PD) and Alzheimer disease (AD) derives from the same network pathology. METHODS: We analyzed 18F-fluorodeoxyglucose PET scans from 40 patients with AD and 40 age-matched healthy controls from the Alzheimer's Disease Neuroimaging Initiative and scanned an additional 10 patients with AD and 10 healthy controls at The Feinstein Institute for Medical Research to derive an AD-related metabolic pattern (ADRP) analogous to our previously established PD cognition-related pattern (PDCP) and PD motor-related pattern (PDRP). We computed individual subject expression values for ADRP and PDCP in 89 patients with PD and correlated summary scores for cognitive functioning with network expression. We also evaluated changes in ADRP and PDCP expression in a separate group of 15 patients with PD scanned serially over a 4-year period. RESULTS: Analysis revealed a significant AD-related metabolic topography characterized by covarying metabolic reductions in the hippocampus, parahippocampal gyrus, and parietal and temporal association regions. Expression of ADRP, but not PDCP, was elevated in both AD groups and correlated with worse cognitive summary scores. Patients with PD showed slight ADRP expression, due to topographic overlap with the network underlying PD motor-related pattern degeneration, but only their PDCP expression values increased as cognitive function and executive performance declined. Longitudinal data in PD disclosed an analogous dissociation of network expression. CONCLUSIONS: Cognitive dysfunction in PD is associated with a specific brain network that is largely spatially and functionally distinct from that seen in relation to AD.

Automated Differential Diagnosis of Early Parkinsonism Using Metabolic Brain Networks: A Validation Study.

UNLABELLED: The differentiation of idiopathic Parkinson disease (IPD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), the most common atypical parkinsonian look-alike syndromes (APS), can be clinically challenging. In these disorders, diagnostic inaccuracy is more frequent early in the clinical course when signs and symptoms are mild. Diagnostic inaccuracy may be particularly relevant in trials of potential disease-modifying agents, which typically involve participants with early clinical manifestations. In an initial study, we developed a probabilistic algorithm to classify subjects with clinical parkinsonism but uncertain diagnosis based on the expression of metabolic covariance patterns for IPD, MSA, and PSP. Classifications based on this algorithm agreed closely with final clinical diagnosis. Nonetheless, blinded prospective validation is required before routine use of the algorithm can be considered. METHODS: We used metabolic imaging to study an independent cohort of 129 parkinsonian subjects with uncertain diagnosis; 77 (60%) had symptoms for 2 y or less at the time of imaging. After imaging, subjects were followed by blinded movement disorders specialists for an average of 2.2 y before final diagnosis was made. When the algorithm was applied to the individual scan data, the probabilities of IPD, MSA, and PSP were computed and used to classify each of the subjects. The resulting image-based classifications were then compared with the final clinical diagnosis. RESULTS: IPD subjects were distinguished from APS with 94% specificity and 96% positive predictive value (PPV) using the original 2-level logistic classification algorithm. The algorithm achieved 90% specificity and 85% PPV for MSA and 94% specificity and 94% PPV for PSP. The diagnostic accuracy was similarly high (specificity and PPV > 90%) for parkinsonian subjects with short symptom duration. In addition, 25 subjects were classified as level I indeterminate parkinsonism and 4 more subjects as level II indeterminate APS. CONCLUSION: Automated pattern-based image classification can improve the diagnostic accuracy in patients with parkinsonism, even at early disease stages.

Rodent models of neuroinflammation for Alzheimer's disease.

Alzheimer's disease remains incurable, and the failures of current disease-modifying strategies for Alzheimer's disease could be attributed to a lack of in vivo models that recapitulate the underlying etiology of late-onset Alzheimer's disease. The etiology of late-onset Alzheimer's disease is not based on mutations related to amyloid-ß (Aß) or tau production which are currently the basis of in vivo models of Alzheimer's disease. It has recently been suggested that mechanisms like chronic neuroinflammation may occur prior to amyloid-ß and tau pathologies in late-onset Alzheimer's disease. The aim of this study is to analyze the characteristics of rodent models of neuroinflammation in late-onset Alzheimer's disease. Our search criteria were based on characteristics of an idealistic disease model that should recapitulate causes, symptoms, and lesions in a chronological order similar to the actual disease. Therefore, a model based on the inflammation hypothesis of late-onset Alzheimer's disease should include the following features: (i) primary chronic neuroinflammation, (ii) manifestations of memory and cognitive impairment, and (iii) late development of tau and Aß pathologies. The following models fit the pre-defined criteria: lipopolysaccharide- and PolyI:C-induced models of immune challenge; streptozotocin-, okadaic acid-, and colchicine neurotoxin-induced neuroinflammation models, as well as interleukin-1ß, anti-nerve growth factor and p25 transgenic models. Among these models, streptozotocin, PolyI:C-induced, and p25 neuroinflammation models are compatible with the inflammation hypothesis of Alzheimer's disease.

Metabolic resting-state brain networks in health and disease.

The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson's disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the "DMN-like" dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer's disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer's disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease.

Neuronal injury and cytogenesis after simple febrile seizures in the hippocampal dentate gyrus of juvenile rat.

PURPOSE: Although simple febrile seizures are frequently described as harmless, there is evidence which suggests that hippocampal damage may occur after simple febrile seizures. This study aimed to investigate possible neuronal damages as well as alterations in cytogenesis in the hippocampal dentate gyrus following simple febrile seizures. METHODS: Simple febrile seizure was modeled by hyperthermia-induced seizures in 22-day-old male rats. The brains were removed 2 or 15 days after hyperthermia in all rats with (n=20) and without (n=10) occurrence of seizures as well as in control animals (n=10). The sections were stained with hematoxylin and eosin to estimate the surface numerical density of dark neurons. Ki-67 immunohistochemistry was performed to evaluate changes of cytogenesis following simple febrile seizures. RESULTS: Hyperthermia induced behavioral seizure activities in 67 % of the rats. The numerical densities of dark neurons as well as the mean Ki-67 index (the fraction of Ki-67-positive cells) were significantly increased in dentate gyrus after induction of seizures by hyperthermia compared to both controls and rats without seizure after hyperthermia. Both the seizure duration and intensity were correlated significantly with numerical densities of dark neurons (but not with Ki-67 index). CONCLUSION: The data indicate that simple febrile seizures can cause neuronal damages and enhancement of cytogenesis in the hippocampal dentate gyrus, which were still visible for at least 2 weeks. These findings also suggest the correlation of febrile seizure intensity and duration with neuronal damage.

Nanotechnology solutions for Alzheimer's disease: advances in research tools, diagnostic methods and therapeutic agents.

A century of research has passed since the discovery and definition of Alzheimer's disease (AD), the primary common dementing disorder worldwide. However, AD lacks definite diagnostic approaches and effective cure at the present. Moreover, the currently available diagnostic tools are not sufficient for an early screening of AD in order to start preventive approaches. Recently the emerging field of nanotechnology has promised new techniques to solve some of the AD challenges. Nanotechnology refers to the techniques of designing and manufacturing nanosize (1-100 nm) structures through controlled positional and/or self-assembly of atoms and molecules. In this report, we present the promises that nanotechnology brings in research on the AD diagnosis and therapy. They include its potential for the better understanding of the AD root cause molecular mechanisms, AD's early diagnoses, and effective treatment. The advances in AD research offered by the atomic force microscopy, single molecule fluorescence microscopy and NanoSIMS microscopy are examined here. In addition, the recently proposed applications of nanotechnology for the early diagnosis of AD including bio-barcode assay, localized surface plasmon resonance nanosensor, quantum dot and nanomechanical cantilever arrays are analyzed. Applications of nanotechnology in AD therapy including neuroprotections against oxidative stress and anti-amyloid therapeutics, neuroregeneration and drug delivery beyond the blood brain barrier (BBB) are discussed and analyzed. All of these applications could improve the treatment approach of AD and other neurodegenerative diseases. The complete cure of AD may become feasible by a combination of nanotechnology and some other novel approaches, like stem cell technology.