934 resultados para Brain image classification
Resumo:
Craniosynostosis consists of a premature fusion of the sutures in an infant skull that restricts skull and brain growth. During the last decades, there has been a rapid increase of fundamentally diverse surgical treatment methods. At present, the surgical outcome has been assessed using global variables such as cephalic index, head circumference, and intracranial volume. However, these variables have failed in describing the local deformations and morphological changes that may have a role in the neurologic disorders observed in the patients. This report describes a rigid image registration-based method to evaluate outcomes of craniosynostosis surgical treatments, local quantification of head growth, and indirect intracranial volume change measurements. The developed semiautomatic analysis method was applied to computed tomography data sets of a 5-month-old boy with sagittal craniosynostosis who underwent expansion of the posterior skull with cranioplasty. Quantification of the local changes between pre- and postoperative images was quantified by mapping the minimum distance of individual points from the preoperative to the postoperative surface meshes, and indirect intracranial volume changes were estimated. The proposed methodology can provide the surgeon a tool for the quantitative evaluation of surgical procedures and detection of abnormalities of the infant skull and its development.
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Music consists of sound sequences that require integration over time. As we become familiar with music, associations between notes, melodies, and entire symphonic movements become stronger and more complex. These associations can become so tight that, for example, hearing the end of one album track can elicit a robust image of the upcoming track while anticipating it in total silence. Here, we study this predictive “anticipatory imagery” at various stages throughout learning and investigate activity changes in corresponding neural structures using functional magnetic resonance imaging. Anticipatory imagery (in silence) for highly familiar naturalistic music was accompanied by pronounced activity in rostral prefrontal cortex (PFC) and premotor areas. Examining changes in the neural bases of anticipatory imagery during two stages of learning conditional associations between simple melodies, however, demonstrates the importance of fronto-striatal connections, consistent with a role of the basal ganglia in “training” frontal cortex (Pasupathy and Miller, 2005). Another striking change in neural resources during learning was a shift between caudal PFC earlier to rostral PFC later in learning. Our findings regarding musical anticipation and sound sequence learning are highly compatible with studies of motor sequence learning, suggesting common predictive mechanisms in both domains.
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Current methods to characterize mesenchymal stem cells (MSCs) are limited to CD marker expression, plastic adherence and their ability to differentiate into adipogenic, osteogenic and chondrogenic precursors. It seems evident that stem cells undergoing differentiation should differ in many aspects, such as morphology and possibly also behaviour; however, such a correlation has not yet been exploited for fate prediction of MSCs. Primary human MSCs from bone marrow were expanded and pelleted to form high-density cultures and were then randomly divided into four groups to differentiate into adipogenic, osteogenic chondrogenic and myogenic progenitor cells. The cells were expanded as heterogeneous and tracked with time-lapse microscopy to record cell shape, using phase-contrast microscopy. The cells were segmented using a custom-made image-processing pipeline. Seven morphological features were extracted for each of the segmented cells. Statistical analysis was performed on the seven-dimensional feature vectors, using a tree-like classification method. Differentiation of cells was monitored with key marker genes and histology. Cells in differentiation media were expressing the key genes for each of the three pathways after 21 days, i.e. adipogenic, osteogenic and chondrogenic, which was also confirmed by histological staining. Time-lapse microscopy data were obtained and contained new evidence that two cell shape features, eccentricity and filopodia (= 'fingers') are highly informative to classify myogenic differentiation from all others. However, no robust classifiers could be identified for the other cell differentiation paths. The results suggest that non-invasive automated time-lapse microscopy could potentially be used to predict the stem cell fate of hMSCs for clinical application, based on morphology for earlier time-points. The classification is challenged by cell density, proliferation and possible unknown donor-specific factors, which affect the performance of morphology-based approaches. Copyright © 2012 John Wiley & Sons, Ltd.
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Neurodegenerative diseases affect the cerebellum of numerous dog breeds. Although subjective, magnetic resonance (MR) imaging has been used to detect cerebellar atrophy in these diseases, but there are few data available on the normal size range of the cerebellum relative to other brain regions. The purpose of this study was to determine whether the size of the cerebellum maintains a consistent ratio with other brain regions in different ages and breeds of normal dogs and to define a measurement that can be used to identify cerebellar atrophy on MR images. Images from 52 normal and 13 dogs with cerebellar degenerative diseases were obtained. Volume and mid-sagittal cross-sectional area of the forebrain, brainstem, and cerebellum were calculated for each normal dog and compared between different breeds and ages as absolute and relative values. The ratio of the cerebellum to total brain and of the brainstem to cerebellum mid-sagittal cross-sectional area was compared between normal and affected dogs and the sensitivity and specificity of these ratios at distinguishing normal from affected dogs was calculated. The percentage of the brain occupied by the cerebellum in diverse dog breeds between 1 and 5 years of age was not significantly different, and cerebellar size did not change with increasing age. Using a cut off of 89%, the ratio between the brainstem and cerebellum mid-sagittal cross-sectional area could be used successfully to differentiate affected from unaffected dogs with a sensitivity and specificity of 100%, making this ratio an effective tool for identifying cerebellar atrophy on MR images.
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The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.
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Proton magnetic resonance spectroscopy (MRS) allows the assessment of various cerebral metabolites non-invasively in vivo. Among 1H MRS-detectable metabolites, N-acetyl-aspartate and N-acetyl-aspartyl-glutamate (tNAA), trimethylamines (TMA), creatine and creatine phosphate (tCr), inositol (Ins) and glutamate (Gla) are of particular interest, since these moieties can be assigned to specific neuronal and glial metabolic pathways, membrane constituents, and energy metabolism. In this study on 94 subjects from a memory clinic population, 1H MRS results (single voxel STEAM: TE 20 ms, TR 1500 ms) on the above metabolites were assessed for five different brain regions in probable vascular dementia (VD), probable Alzheimer's disease (AD), and age-matched healthy controls. In both VD and AD, ratios of tNAA/tCr were decreased, which may be attributed to neuronal atrophy and loss, and Ins/tCr-ratios were increased indicating either enhanced gliosis or alteration of the cerebral inositol metabolism. However, the topographical distribution of the metabolic alterations in both diseases differed, revealing a temporoparietal pattern for AD and a global, subcortically pronounced pattern for VD. Furthermore, patients suffering from vascular dementia (VD) had remarkably enhanced TMA/tCr ratios, potentially due to ongoing degradation of myelin. Thus, the metabolic alterations obtained by 1H MRS in vivo allow insights into the pathophysiology of the different dementias and may be useful for diagnostic classification.
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OBJECT: In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors. METHODS: Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors. CONCLUSIONS: The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.
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Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.
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The blood-brain barrier (BBB) is a highly specialized structural and functional component of the central nervous system that separates the circulating blood from the brain and spinal cord parenchyma. Brain endothelial cells (BECs) that primarily constitute the BBB are tightly interconnected by multiprotein complexes, the adherens junctions and the tight junctions, thereby creating a highly restrictive cellular barrier. Lipid-enriched membrane microdomain compartmentalization is an inherent property of BECs and allows for the apicobasal polarity of brain endothelium, temporal and spatial coordination of cell signaling events, and actin remodeling. In this manuscript, we review the role of membrane microdomains, in particular lipid rafts, in the BBB under physiological conditions and during leukocyte transmigration/diapedesis. Furthermore, we propose a classification of endothelial membrane microdomains based on their function, or at least on the function ascribed to the molecules included in such heterogeneous rafts: (1) rafts associated with interendothelial junctions and adhesion of BECs to basal lamina (scaffolding rafts); (2) rafts involved in immune cell adhesion and migration across brain endothelium (adhesion rafts); (3) rafts associated with transendothelial transport of nutrients and ions (transporter rafts).
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When we actively explore the visual environment, our gaze preferentially selects regions characterized by high contrast and high density of edges, suggesting that the guidance of eye movements during visual exploration is driven to a significant degree by perceptual characteristics of a scene. Converging findings suggest that the selection of the visual target for the upcoming saccade critically depends on a covert shift of spatial attention. However, it is unclear whether attention selects the location of the next fixation uniquely on the basis of global scene structure or additionally on local perceptual information. To investigate the role of spatial attention in scene processing, we examined eye fixation patterns of patients with spatial neglect during unconstrained exploration of natural images and compared these to healthy and brain-injured control participants. We computed luminance, colour, contrast, and edge information contained in image patches surrounding each fixation and evaluated whether they differed from randomly selected image patches. At the global level, neglect patients showed the characteristic ipsilesional shift of the distribution of their fixations. At the local level, patients with neglect and control participants fixated image regions in ipsilesional space that were closely similar with respect to their local feature content. In contrast, when directing their gaze to contralesional (impaired) space neglect patients fixated regions of significantly higher local luminance and lower edge content than controls. These results suggest that intact spatial attention is necessary for the active sampling of local feature content during scene perception.
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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.
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BrainMaps.org is an interactive high-resolution digital brain atlas and virtual microscope that is based on over 20 million megapixels of scanned images of serial sections of both primate and non-primate brains and that is integrated with a high-speed database for querying and retrieving data about brain structure and function over the internet. Complete brain datasets for various species, including Homo sapiens, Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, and Tyto alba, are accessible online. The methods and tools we describe are useful for both research and teaching, and can be replicated by labs seeking to increase accessibility and sharing of neuroanatomical data. These tools offer the possibility of visualizing and exploring completely digitized sections of brains at a sub-neuronal level, and can facilitate large-scale connectional tracing, histochemical and stereological analyses.
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BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.
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Covert brain activity related to task-free, spontaneous (i.e. unrequested), emotional evaluation of human face images was analysed in 27-channel averaged event-related potential (ERP) map series recorded from 18 healthy subjects while observing random sequences of face images without further instructions. After recording, subjects self-rated each face image on a scale from “liked” to “disliked”. These ratings were used to dichotomize the face images into the affective evaluation categories of “liked” and “disliked” for each subject and the subjects into the affective attitudes of “philanthropists” and “misanthropists” (depending on their mean rating across images). Event-related map series were averaged for “liked” and “disliked” face images and for “philanthropists” and “misanthropists”. The spatial configuration (landscape) of the electric field maps was assessed numerically by the electric gravity center, a conservative estimate of the mean location of all intracerebral, active, electric sources. Differences in electric gravity center location indicate activity of different neuronal populations. The electric gravity center locations of all event-related maps were averaged over the entire stimulus-on time (450 ms). The mean electric gravity center for disliked faces was located (significant across subjects) more to the right and somewhat more posterior than for liked faces. Similar differences were found between the mean electric gravity centers of misanthropists (more right and posterior) and philanthropists. Our neurophysiological findings are in line with neuropsychological findings, revealing visual emotional processing to depend on affective evaluation category and affective attitude, and extending the conclusions to a paradigm without directed task.
Resumo:
Objective: Identification of the ventrointermediate thalamic nucleus (Vim) in modern 3T high-field MRI for image-based targeting in deep brain stimulation (DBS) is still challenging. To evaluate the usefulness and reliability of analyzing the connectivity with the cerebellum using Q-ball-calculation we performed a retrospective analysis. Method: 5 patients who underwent bilateral implantation of electrodes in the Vim for treatment of Essential Tremor between 2011 and 2012 received additional preoperative Q-ball imaging. Targeting was performed according to atlas coordinates and standard MRI. Additionally we performed a retrospective identification of the Vim by analyzing the connectivity of the thalamus with the dentate nucleus. The exact position of the active stimulation contact in the postoperative CT was correlated with the Vim as it was identified by Q-ball calculation. Results: Localization of the Vim by analysis of the connectivity between thalamus and cerebellum was successful in all 5 patients on both sides. The average position of the active contacts was 14.6 mm (SD 1.24) lateral, 5.37 mm (SD 0.094 posterior and 2.21 mm (SD 0.69) cranial of MC. The cranial portion of the dentato-rubro-thalamic tract was localized an average of 3.38 mm (SD 1.57) lateral and 1.5 mm (SD 1.22) posterior of the active contact. Conclusions: Connectivity analysis by Q-ball calculation provided direct visualization of the Vim in all cases. Our preliminary results suggest, that the target determined by connectivity analysis is valid and could possibly be used in addition to or even instead of atlas based targeting. Larger prospective calculations are needed to determine the robustness of this method in providing refined information useful for neurosurgical treatment of tremor.