986 resultados para Brain areas
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Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox functionalities were used to study AD by T1weighted, Diffusion Tensor Imaging and 18FAV45 PET, with data obtained from the AD Neuroimaging Initiative database, specifically 12 healthy controls (CTRL) and 33 patients with early mild cognitive impairment (EMCI), late MCI (LMCI) and AD (11 patients/group). The metrics evaluated were gray-matter volume (GMV), cortical thickness (CThk), mean diffusivity (MD), fractional anisotropy (FA), fiber count (FiberConn), node degree (Deg), cluster coefficient (ClusC) and relative standard-uptake-values (rSUV). Receiver Operating Characteristic (ROC) curves were used to evaluate and compare the diagnostic accuracy of the most significant metrics and brain regions and expressed as area under the curve (AUC). Comparisons were performed between groups. The RH-Accumbens/Deg demonstrated the highest AUC when differentiating between CTRLEMCI (82%), whether rSUV presented it in several brain regions when distinguishing CTRL-LMCI (99%). Regarding CTRL-AD, highest AUC were found with LH-STG/FiberConn and RH-FP/FiberConn (~100%). A larger number of neuroimaging metrics related with cortical atrophy with AUC>70% was found in CTRL-AD in both hemispheres, while in earlier stages, cortical metrics showed in more confined areas of the temporal region and mainly in LH, indicating an increasing of the spread of cortical atrophy that is characteristic of disease progression. In CTRL-EMCI several brain regions and neuroimaging metrics presented AUC>70% with a worst result in later stages suggesting these indicators as biomarkers for an earlier stage of MCI, although further research is necessary.
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Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers
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Brain dopamine transporters imaging by Single Emission Tomography (SPECT) with 123I-FP-CIT (DaTScanTM) has become an important tool in the diagnosis and evaluation of Parkinson syndromes.This diagnostic method allows the visualization of a portion of the striatum – where healthy pattern resemble two symmetric commas - allowing the evaluation of dopamine presynaptic system, in which dopamine transporters are responsible for dopamine release into the synaptic cleft, and their reabsorption into the nigrostriatal nerve terminals, in order to be stored or degraded. In daily practice for assessment of DaTScan TM, it is common to rely only on visual assessment for diagnosis. However, this process is complex and subjective as it depends on the observer’s experience and it is associated with high variability intra and inter observer. Studies have shown that semiquantification can improve the diagnosis of Parkinson syndromes. For semiquantification, analysis methods of image segmentation using regions of interest (ROI) are necessary. ROIs are drawn, in specific - striatum - and in nonspecific – background – uptake areas. Subsequently, specific binding ratios are calculated. Low adherence of semiquantification for diagnosis of Parkinson syndromes is related, not only with the associated time spent, but also with the need of an adapted database of reference values for the population concerned, as well as, the examination of each service protocol. Studies have concluded, that this process increases the reproducibility of semiquantification. The aim of this investigation was to create and validate a database of healthy controls for Dopamine transporters with DaTScanTM named DBRV. The created database has been adapted to the Nuclear Medicine Department’s protocol, and the population of Infanta Cristina’s Hospital located in Badajoz, Spain.
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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).
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Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical Engineering
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The currently available clinical imaging methods do not provide highly detailed information about location and severity of axonal injury or the expected recovery time of patients with traumatic brain injury [1]. High-Definition Fiber Tractography (HDFT) is a novel imaging modality that allows visualizing and quantifying, directly, the degree of axons damage, predicting functional deficits due to traumatic axonal injury and loss of cortical projections. This imaging modality is based on diffusion technology [2]. The inexistence of a phantom able to mimic properly the human brain hinders the possibility of testing, calibrating and validating these medical imaging techniques. Most research done in this area fails in key points, such as the size limit reproduced of the brain fibers and the quick and easy reproducibility of phantoms [3]. For that reason, it is necessary to develop similar structures matching the micron scale of axon tubes. Flexible textiles can play an important role since they allow producing controlled packing densities and crossing structures that match closely the human crossing patterns of the brain. To build a brain phantom, several parameters must be taken into account in what concerns to the materials selection, like hydrophobicity, density and fiber diameter, since these factors influence directly the values of fractional anisotropy. Fiber cross-section shape is other important parameter. Earlier studies showed that synthetic fibrous materials are a good choice for building a brain phantom [4]. The present work is integrated in a broader project that aims to develop a brain phantom made by fibrous materials to validate and calibrate HDFT. Due to the similarity between thousands of hollow multifilaments in a fibrous arrangement, like a yarn, and the axons, low twist polypropylene multifilament yarns were selected for this development. In this sense, extruded hollow filaments were analysed in scanning electron microscope to characterize their main dimensions and shape. In order to approximate the dimensional scale to human axons, five types of polypropylene yarns with different linear density (denier) were used, aiming to understand the effect of linear density on the filament inner and outer areas. Moreover, in order to achieve the required dimensions, the polypropylene filaments cross-section was diminished in a drawing stage of a filament extrusion line. Subsequently, tensile tests were performed to characterize the mechanical behaviour of hollow filaments and to evaluate the differences between stretched and non-stretched filaments. In general, an increase of the linear density causes the increase in the size of the filament cross section. With the increase of structure orientation of filaments, induced by stretching, breaking tenacity increases and elongation at break decreases. The production of hollow fibers, with the required characteristics, is one of the key steps to create a brain phantom that properly mimics the human brain that may be used for the validation and calibration of HDFT, an imaging approach that is expected to contribute significantly to the areas of brain related research.
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Normal visual perception requires differentiating foreground from background objects. Differences in physical attributes sometimes determine this relationship. Often such differences must instead be inferred, as when two objects or their parts have the same luminance. Modal completion refers to such perceptual "filling-in" of object borders that are accompanied by concurrent brightness enhancement, in turn termed illusory contours (ICs). Amodal completion is filling-in without concurrent brightness enhancement. Presently there are controversies regarding whether both completion processes use a common neural mechanism and whether perceptual filling-in is a bottom-up, feedforward process initiating at the lowest levels of the cortical visual pathway or commences at higher-tier regions. We previously examined modal completion (Murray et al., 2002) and provided evidence that the earliest modal IC sensitivity occurs within higher-tier object recognition areas of the lateral occipital complex (LOC). We further proposed that previous observations of IC sensitivity in lower-tier regions likely reflect feedback modulation from the LOC. The present study tested these proposals, examining the commonality between modal and amodal completion mechanisms with high-density electrical mapping, spatiotemporal topographic analyses, and the local autoregressive average distributed linear inverse source estimation. A common initial mechanism for both types of completion processes (140 msec) that manifested as a modulation in response strength within higher-tier visual areas, including the LOC and parietal structures, is demonstrated, whereas differential mechanisms were evident only at a subsequent time period (240 msec), with amodal completion relying on continued strong responses in these structures.
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Neural stem cells have been proposed as a new and promising treatment modality in various pathologies of the central nervous system, including malignant brain tumors. However, the underlying mechanism by which neural stem cells target tumor areas remains elusive. Monitoring of these cells is currently done by use of various modes of molecular imaging, such as optical imaging, magnetic resonance imaging and positron emission tomography, which is a novel technology for visualizing metabolism and signal transduction to gene expression. In this new context, the microenvironment of (malignant) brain tumors and the blood-brain barrier gains increased interest. The authors of this review give a unique overview of the current molecular-imaging techniques used in different therapeutic experimental brain tumor models in relation to neural stem cells. Such methods for molecular imaging of gene-engineered neural stem/progenitor cells are currently used to trace the location and temporal level of expression of therapeutic and endogenous genes in malignant brain tumors, closing the gap between in vitro and in vivo integrative biology of disease in neural stem cell transplantation.
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Brain-derived neurotrophic factor (BDNF) promotes synaptic plasticity via an enhancement in expression of specific synaptic proteins. Recent results suggest that the neuronal monocarboxylate transporter MCT2 is a postsynaptic protein critically involved in synaptic plasticity and long-term memory. To investigate in vivo whether BDNF can modulate the expression of MCT2 as well as other proteins involved in synaptic plasticity, acute injection of BDNF was performed in mouse dorsal hippocampal CA1 area. Using immunohistochemistry, it was found that MCT2 expression was enhanced in part of the CA1 area and in the dentate gyrus 6 h after a single intrahippocampal injection of BDNF. Similarly, expression of the immediate early genes Arc and Zif268 was enhanced in the same hippocampal areas, in accordance with their role in synaptic plasticity. Immunoblot analysis confirmed the significant enhancement in MCT2 protein expression. In contrast, no changes were observed for the glial monocarboxylate transporters MCT1 and MCT4. When other synaptic proteins were investigated, it was found that postsynaptic density 95 (PSD95) and glutamate receptor 2 (GluR2) protein levels were significantly enhanced while no effect could be detected for synaptophysin, synaptosomal-associated protein 25 (SNAP25), αCaMKII and GluR1. These results demonstrate that MCT2 expression can be upregulated together with other key postsynaptic proteins in vivo under conditions related to synaptic plasticity, further suggesting the importance of energetics for memory formation.
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den Dunnen et al. [den Dunnen, W.F.A., Brouwer, W.H., Bijlard, E., Kamphuis, J., van Linschoten, K., Eggens-Meijer, E., Holstege, G., 2008. No disease in the brain of a 115-year-old woman. Neurobiol. Aging] had the opportunity to follow up the cognitive functioning of one of the world's oldest woman during the last 3 years of her life. They performed two neuropsychological evaluations at age 112 and 115 that revealed a striking preservation of immediate recall abilities and orientation. In contrast, working memory, retrieval from semantic memory and mental arithmetic performances declined after age 112. Overall, only a one-point decrease of MMSE score occurred (from 27 to 26) reflecting the remarkable preservation of cognitive abilities. The neuropathological assessment showed few neurofibrillary tangles (NFT) in the hippocampal formation compatible with Braak staging II, absence of amyloid deposits and other types of neurodegenerative lesions as well as preservation of neuron numbers in locus coeruleus. This finding was related to a striking paucity of Alzheimer disease (AD)-related lesions in the hippocampal formation. The present report parallels the early descriptions of rare "supernormal" centenarians supporting the dissociation between brain aging and AD processes. In conjunction with recent stereological analyses in cases aged from 90 to 102 years, it also points to the marked resistance of the hippocampal formation to the degenerative process in this age group and possible dissociation between the occurrence of slight cognitive deficits and development of AD-related pathologic changes in neocortical areas. This work is discussed in the context of current efforts to identify the biological and genetic parameters of human longevity.
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BACKGROUND: We aimed to study the incidence and outcome of severe traumatic brain injury (TBI) in Switzerland and to test the feasibility of a large cohort study with case identification in the first 24 hours and 6-month follow-up. METHODS: From January to June 2005, we consecutively enrolled and followed up all persons with severe TBI (Abbreviated Injury Score of the head region >3 and Glasgow Coma Scale <9) in the catchment areas of 3 Swiss medical centres with neurosurgical facilities. The primary outcome was the Extended Glasgow Outcome Scale (GOSE) after 6 months. Secondary outcomes included survival, Functional Independence Mea - sure (FIM), and health-related quality of life (SF-12) at defined time-points up to 6 months after injury. RESULTS: We recruited 101 participants from a source population of about 2.47 million (ie, about 33% of Swiss population). The incidence of severe TBI was 8.2 per 100,000 person-years. The overall case fatality was 70%: 41 of 101 persons (41%) died at the scene of the accident. 23 of 60 hospitalised participants (38%) died within 48 hours, and 31 (53%) within 6 months. In all hospitalised patients, the median GOSE was 1 (range 1-8) after 6 months, and was 6 (2-8) in 6-month survivors. The median total FIM score was 125 (range 18-126); median-SF-12 component mea - sures were 44 (25-55) for the physical scale and 52 (32-65) for the mental scale. CONCLUSIONS: Severe TBI was associated with high case fatality and considerable morbidity in survivors. We demonstrated the feasibility of a multicentre cohort study in Switzerland with the aim of identifying modifiable determinants of outcome and improving current trauma care.
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Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.
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The purpose of this review is to critically appraise the pain assessment tools for non communicative persons in intensive care available in the literature and to determine their relevance for those with brain injury. Nursing and medical electronic databases were searched to identify pain tools, with a description of psychometric proprieties, in English and French. Seven of the ten tools were considered relevant and systematically evaluated according to the criteria and the indicators in the following five areas: conceptualisation, target population, feasibility and clinical utility, reliability and validity. Results indicate a number of well designed pain tools, but additional work is necessary to establish their accuracy and adequacy for the brain injured non communicative person in intensive care. Recommendations are made to choose the best tool for clinical practice and for research.
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The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.
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Global left ventricular (LV) systolic dysfunction is the strongest predictor of morbidity and mortality in Chagas disease. Echocardiography is considered the gold standard for the detection of LV dysfunction, but not always available in endemic areas where chagasic cardiomyopathy is most common. Brain natriuretic peptide (BNP) is a neurohormone that has been recently described as a simple and inexpensive diagnostic and prognostic marker for patients with congestive heart failure. Chagasic patients (n = 63) and non-infected healthy individuals (n = 18) were recruited prospectively and underwent complete clinical examination, echocardiography and 24-h Holter monitoring. BNP was measured from thawed plasma samples using the Triage BNP test. We observed high levels of BNP in association with depression of LV ejection fraction, with increase of LV end-diastolic diameter and with LV premature complexes. An elevated concentration of BNP, defined as a concentration of 60 pg/ml or more, had a sensitivity of 91.7%, specificity of 82.8%, positive predictive value of 52.4%, and negative predictive value of 98% for detecting LV dysfunction (LV ejection fraction < 40%).BNP measurement using a simple, relatively inexpensive and rapid test has a promising role in identifying LV dysfunction associated with chagasic cardiomyopathy. Equally important, patients with Trypanosoma cruzi infection who have low levels of BNP level in plasma have a very low likelihood of severe cardiac involvement, and echocardiography is probably not necessary.