Delayed Cyclic Activity Development on Early Amplitude-Integrated EEG in the Preterm Infant with Brain Lesions.

Background: Maturation of amplitude-integrated electroencephalogram (aEEG) activity is influenced by both gestational age (GA) and postmenstrual age. It is not fully known how this process is influenced by cerebral lesions. Objective: To compare early aEEG developmental changes between preterm newborns with different degrees of cerebral lesions on cranial ultrasound (cUS). Methods: Prospective cohort study on preterm newborns with GA <32.0 weeks, undergoing continuous aEEG recording during the first 84 h after birth. aEEG characteristics were qualitatively and quantitatively evaluated using pre-established criteria. Based on cUS findings three groups were formed: normal (n = 78), mild (n = 20), and severe cerebral lesions (n = 6). Linear mixed models for repeated measures were used to analyze aEEG maturational trajectories. Results: 104 newborns with a mean GA (range) 29.5 (24.4-31.7) weeks, and birth weight 1,220 (580-2,020) g were recruited. Newborns with severe brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p < 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant.

In vivo 13C NMR spectroscopy and metabolic modeling in the brain: a practical perspective.

In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.

Lactate and the injured brain: friend or foe?

PURPOSE OF REVIEW: Energy metabolism is increasingly recognized as a key factor in the pathogenesis of acute brain injury (ABI). We review the role of cerebral lactate metabolism and summarize evidence showing that lactate may act as supplemental fuel after ABI. RECENT FINDINGS: The role of cerebral lactate has shifted from a waste product to a potentially preferential fuel and signaling molecule. According to the astrocyte-neuron lactate shuttle model, glycolytic lactate might act as glucose-sparing substrate. Lactate also is emerging as a key signal to regulate cerebral blood flow (CBF) and a neuroprotective agent after experimental ABI. Clinical investigation using cerebral microdialysis shows the existence of two main lactate patterns, ischemic - from anaerobic metabolism - and nonischemic, from activated glycolysis, whereby lactate can be used as supplemental energy fuel. Preliminary clinical data suggests hypertonic lactate solutions improve cerebral energy metabolism and are an effective treatment for elevated intracranial pressure (ICP) after ABI. SUMMARY: Lactate can be a supplemental fuel for the injured brain and is important to regulate glucose metabolism and CBF. Exogenous lactate supplementation may be neuroprotective after experimental ABI. Recent clinical data from ABI patients suggest hypertonic lactate solutions may be a valid therapeutic option for secondary energy dysfunction and elevated ICP.

Laser scanning evaluation of atrophy after autologous free muscle transfer.

Denervated muscle tissue undergoes morphologic changes that result in atrophy. The amount of muscle atrophy after denervation following free muscle transfer has not been measured so far. Therefore, the amount of muscle atrophy in human free muscle transfer for lower extremity reconstruction was measured in a series of 10 patients. Three-dimensional laser surface scanning was used to measure flap volume changes 2 weeks as well as 6 and 12 months after the operation. None of the muscles transferred was re-innervated.All muscles healed uneventfully without signs of compromised perfusion resulting in partial flap loss. The muscle volume decreased to 30 ± 4% and 19 ± 4% 6 and 12 months, respectively, after the operation, ie, the volume decreased by approximately 80% within a 12-month period.Denervated free muscle flap tissue undergoes massive atrophy of approximately 80%, mostly within the first 6 months.

Brain Spectrins 240/235 and 240/235E: Differential Expression During Development of Chicken Dorsal Root Ganglia in vivo and in vitro.

Brain spectrin, a membrane-related cytoskeletal protein, exists as two isoforms. Brain spectrin 240/235 is localized preferentially in the perikaryon and axon of neuronal cells and brain spectrin 240/235E is found essentially in the neuronal soma and dendrites and in glia (Riederer et al., 1986, J. Cell Biol., 102, 2088 - 2097). The sensory neurons in dorsal root ganglia, devoid of any dendrites, make a good tool to investigate such differential expression of spectrin isoforms. In this study expression and localization of both brain spectrin isoforms were analysed during early chicken dorsal root ganglia development in vivo and in culture. Both isoforms appeared at embryonic day 6. Brain spectrin 240/235 exhibited a transient increase during embryonic development and was first expressed in ventrolateral neurons. In ganglion cells in situ and in culture this spectrin type showed a somato - axonal distribution pattern. In contrast, brain spectrin 240/235E slightly increased between E6 and E15 and remained practically unchanged. It was localized mainly in smaller neurons of the mediodorsal area as punctate staining in the cytoplasm, was restricted exclusively to the ganglion cell perikarya and was absent from axons both in situ and in culture. This study suggests that brain spectrin 240/235 may contribute towards outgrowth, elongation and maintenance of axonal processes and that brain spectrin 240/235E seems to be exclusively involved in the stabilization of the cytoarchitecture of cell bodies in a selected population of ganglion cells.

Subplate subpopulations in the hypoxic-ischemic neonatal rat brain

Subplate neurons are among the earliest born cells of the neocortex and play a fundamental role in cortical development, in particular in the formation of thalamocortical connections. Subplate abnormalities have been described in several neuropathological disorders including schizophrenia, autism and periventricular eukomalacia (Eastwood and Harrison, Schizophr Res, 79, 2005; McQuillen and Ferriero, Brain Pathol, 15, 2005). We have identified and confirmed a range of specific markers for murine subplate using a microarray based approach and found that different subplate subpopulations are characterized by distinct expression patterns of these genes (Hoerder-Suabedissen et al., Cereb Cortex, 19, 2009). In this current study, we are making use of these markers to investigate neuropathological changes of the subplate after cerebral hypoxia-ischemia (HI) in the neonatal rat. First, we characterized the expression of a number of murine subplate markers in the postnatal rat using immunohistochemistry and in situ hybridization. While several genes (Nurr1, Cplx3, Ctgf and Tmem163) presented very similar expression patterns as in the mouse, others (Ddc, MoxD1 and TRH) were completely absent in the rat cortex. This finding suggests important differences in the subplate populations of these two rodent species. In a neonatal rat model of HI, selective vulnerability of subplate has been suggested using BrdU birthdating methods (McQuillen et al., J Neurosci, 15, 2003). We hypothesized that certain subplate subpopulations could be more susceptible than others and analyzed the above subplate markers in a similar yet slightly milder HI model. Two-day old male rat pups underwent permanent occlusion of the right common carotid artery followed by a period of hypoxia (6% O2, 1.5h or 2h) and were analyzed six days later. Preliminary counts on three subplate subpopulations (Nurr1+, Cplx3+ and Ctgf+ cells, respectively) showed similar reductions in cell numbers for all three groups. In addition, we found that the majority of cases which show changes in the subplate also exhibit lesions in the deep cortical layers VI (identified by FoxP2 expression) and sometimes even layer V (revealed by Er81 immunoreactivity), which questions the selective susceptibility of subplate over other cortical layers under the conditions we used in our model. Supported by MRC, FMO holds a Berrow Scholarship, Lincoln College, Oxford.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

The costs of disorders of the brain in Switzerland: an update from the European Brain Council Study for 2010.

BACKGROUND: In 2005, findings of the first "cost of disorders of the brain in Europe" study of the European Brain Council (EBC) showed that these costs cause a substantial economic burden to the Swiss society. In 2010 an improved update with a broader range of disorders has been analysed. This report shows the new findings for Switzerland and discusses changes. METHODS: Data are derived from the EBC 2010 census study that estimates 12-month prevalence of 12 groups of disorders of the brain and calculates costs (direct health-care costs, direct non-medical costs and indirect costs) by combining top-down and bottom up cost approaches using existing data. RESULTS: The most frequent disorder was headache (2.3 million). Anxiety disorders were found in 1 million persons and sleep disorders in 700,000 persons. Annual costs for all assessed disorders total to 14.5 billion Euro corresponding to about 1,900 EUR per inhabitant per year. Mood, psychotic disorders and dementias (appr. 2 billion EUR each) were most costly. Costs per person were highest for neurological/neurosurgery-relevant disorders, e.g. neuromuscular disorders, brain tumour and multiple sclerosis (38,000 to 24,000 EUR). CONCLUSION: The estimates of the EBC 2010 study for Switzerland provide a basis for health care planning. Increase in size and costs compared to 2005 are mostly due to the inclusion of new disorders (e.g., sleep disorders), or the re-definition of others (e.g., headache) and to an increase in younger cohorts. We suggest coordinated research and preventive measures coordinated between governmental bodies, private health-care and pharmaceutical companies.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.

Evolution of the neurochemical profile after transient focal cerebral ischemia in the mouse brain.

Evolution of the neurochemical profile consisting of 19 metabolites after 30 mins of middle cerebral artery occlusion was longitudinally assessed at 3, 8 and 24 h in 6 to 8 microL volumes in the striatum using localized 1H-magnetic resonance spectroscopy at 14.1 T. Profound changes were detected as early as 3 h after ischemia, which include elevated lactate levels in the presence of significant glucose concentrations, decreases in glutamate and a transient twofold glutamine increase, likely to be linked to the excitotoxic release of glutamate and conversion into glial glutamine. Interestingly, decreases in N-acetyl-aspartate (NAA), as well as in taurine, exceeded those in neuronal glutamate, suggesting that the putative neuronal marker NAA is rather a sensitive marker of neuronal viability. With further ischemia evolution, additional, more profound concentration decreases were detected, reflecting a disruption of cellular functions. We conclude that early changes in markers of energy metabolism, glutamate excitotoxicity and neuronal viability can be detected with high precision non-invasively in mice after stroke. Such investigations should lead to a better understanding and insight into the sequential early changes in the brain parenchyma after ischemia, which could be used for identifying new targets for neuroprotection.

MR connectomics: a conceptual framework for studying the developing brain.

THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.