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Magnetic Resonance Imaging Data (magnetic + resonance_imaging_data)
Selected AbstractsTalairach-Based Parcellation of Neonatal Brain Magnetic Resonance Imaging Data: Validation of a New ApproachJOURNAL OF NEUROIMAGING, Issue 4 2005Haissam Haidar PhD ABSTRACT Background and Purpose. Talairach-based parcellation (TP) of human brain magnetic resonance imaging (MRI) data has been used increasingly in clinical research to make regional measurements of brain structures in vivo. Recently, TP has been applied to pediatric research to elucidate the changes in regional brain volumes related to several neurological disorders. However, all freely available tools have been designed to parcellate adult brain MRI data. Parcellation of neonatal MRI data is very challenging owing to the lack of strong signal contrast, variability in signal intensity within tissues, and the small size and thus difficulty in identifying small structures used as landmarks for TP. Hence the authors designed and validated a new interactive tool to parcellate brain MRI data from newborns and young infants. Methods. The authors' tool was developed as part of a postprocessing pipeline, which includes registration of multichannel MR images, segmentation, and parcellation of the segmented data. The tool employs user-friendly interactive software to visualize and assign the anatomic landmarks required for parcellation, after which the planes and parcels are generated automatically by the algorithm. The authors then performed 3 sets of validation experiments to test the precision and reliability of their tool. Results. Validation experiments of intra-and interrater reliability on data obtained from newborn and 1-year-old children showed a very high sensitivity of >95% and specificity >99.9%. The authors also showed that rotating and reformatting the original MRI data results in a statistically significant difference in parcel volumes, demonstrating the importance of using a tool such as theirs that does not require realignment of the data prior to parcellation. Conclusions. To the authors' knowledge, the presented approach is the first TP method that has been developed and validated specifically for neonatal brain MRI data. Their approach would also be valuable for the analysis of brain MRI data from older children and adults. [source] Aspects of Left Ventricular Morphology Outperform Left Ventricular Mass for Prediction of QRS DurationANNALS OF NONINVASIVE ELECTROCARDIOLOGY, Issue 2 2010Nina Hakacova M.D., Ph.D. Background: The knowledge of the case-specific normal QRS duration in each individual is needed when determining the onset, severity and progression of the heart disease. However, large interindividual variability even of the normal QRS duration exists. The aims of the study were to develop a model for prediction of normal QRS complex duration and to test it on healthy individuals. Methods: The study population of healthy adult volunteers was divided into a sample for development of a prediction model (n = 63) and a testing sample (n = 30). Magnetic resonance imaging data were used to assess anatomical characteristics of the left ventricle: the angle between papillary muscles (PMA), the length of the left ventricle (LVL) and left ventricular mass (LVM). Twelve-lead electrocardiogram (ECG) was used for measurement of the QRS duration. Multiple linear regression analysis was used to develop a prediction model to estimate the QRS duration. The accuracy of the prediction model was assessed by comparing predicted with measured QRS duration in the test set. Results: The angle between PMA and the length of the LVL were statistically significant predictors of QRS duration. Correlation between QRS duration and PMA and LVL was r = 0.57, P = 0.0001 and r = 0.45, P = 0.0002, respectively. The final model for prediction of the QRS was: QRSPredicted= 97 + (0.35 × LVL) , (0.45 × PMA). The predicted and real QRS duration differed with median 1 ms. Conclusions: The model for prediction of QRS duration opens the ability to predict case-specific normal QRS duration. This knowledge can have clinical importance, when determining the normality on case-specific basis. Ann Noninvasive Electrocardiol 2010;15(2):124,129 [source] Estimating the number of independent components for functional magnetic resonance imaging dataHUMAN BRAIN MAPPING, Issue 11 2007Yi-Ou Li Abstract Multivariate analysis methods such as independent component analysis (ICA) have been applied to the analysis of functional magnetic resonance imaging (fMRI) data to study brain function. Because of the high dimensionality and high noise level of the fMRI data, order selection, i.e., estimation of the number of informative components, is critical to reduce over/underfitting in such methods. Dependence among fMRI data samples in the spatial and temporal domain limits the usefulness of the practical formulations of information-theoretic criteria (ITC) for order selection, since they are based on likelihood of independent and identically distributed (i.i.d.) data samples. To address this issue, we propose a subsampling scheme to obtain a set of effectively i.i.d. samples from the dependent data samples and apply the ITC formulas to the effectively i.i.d. sample set for order selection. We apply the proposed method on the simulated data and show that it significantly improves the accuracy of order selection from dependent data. We also perform order selection on fMRI data from a visuomotor task and show that the proposed method alleviates the over-estimation on the number of brain sources due to the intrinsic smoothness and the smooth preprocessing of fMRI data. We use the software package ICASSO (Himberg et al. [ 2004]: Neuroimage 22:1214,1222) to analyze the independent component (IC) estimates at different orders and show that, when ICA is performed at overestimated orders, the stability of the IC estimates decreases and the estimation of task related brain activations show degradation. Hum Brain Mapp, 2007. © 2007 Wiley-Liss, Inc. [source] Bayesian comparison of spatially regularised general linear modelsHUMAN BRAIN MAPPING, Issue 4 2007Will Penny Abstract In previous work (Penny et al., [2005]: Neuroimage 24:350,362) we have developed a spatially regularised General Linear Model for the analysis of functional magnetic resonance imaging data that allows for the characterisation of regionally specific effects using Posterior Probability Maps (PPMs). In this paper we show how it also provides an approximation to the model evidence. This is important as it is the basis of Bayesian model comparison and provides a unified framework for Bayesian Analysis of Variance, Cluster of Interest analyses and the principled selection of signal and noise models. We also provide extensions that implement spatial and anatomical regularisation of noise process parameters. Hum Brain Mapp 2007. © 2006 Wiley-Liss, Inc. [source] Hypothesis testing in distributed source models for EEG and MEG dataHUMAN BRAIN MAPPING, Issue 2 2006Lourens J. Waldorp Abstract Hypothesis testing in distributed source models for the electro- or magnetoencephalogram is generally performed for each voxel separately. Derived from the analysis of functional magnetic resonance imaging data, such a statistical parametric map (SPM) ignores the spatial smoothing in hypothesis testing with distributed source models. For example, when intending to test a single voxel, actually an entire region of voxels is tested simultaneously. Because there are more parameters than observations, typically constraints are employed to arrive at a solution which spatially smooths the solution. If ignored, it can be concluded from the hypothesis test that there is activity at some location where there is none. In addition, an SPM on distributed source models gives the illusion of very high resolution. As an alternative, a multivariate approach is suggested in which a region of interest is tested that is spatially smooth. In simulations with MEG and EEG it is shown that clear hypothesis testing in distributed source models is possible, provided that there is high correspondence between what is intended to be tested and what is actually tested. The approach is also illustrated by an application to data from an experiment measuring visual evoked fields when presenting checkerboard patterns. Hum Brain Mapp, 2005. © 2005 Wiley-Liss, Inc. [source] Blood Oxygen Level Dependent Response and Spatial Working Memory in Adolescents With Alcohol Use DisordersALCOHOLISM, Issue 10 2004Susan F. Tapert Background: Previous studies have suggested neural disruption and reorganization in young and older adults with alcohol use disorders (AUD). However, it remains unclear at what age and when in the progression of AUD changes in brain functioning might occur. Methods: Alcohol use disordered (n= 15) and nonabusing (n= 19) boys and girls aged 15 to 17 were recruited from local high schools. Functional magnetic resonance imaging data were collected after a minimum of 5 days' abstinence as participants performed spatial working memory and simple motor tasks. Results: Adolescents with AUD showed greater brain response to the spatial working memory task in bilateral parietal cortices and diminished response in other regions, including the left precentral gyrus and bilateral cerebellar areas (clusters ,943 ,l; p < 0.05), although groups did not differ on behavioral measures of task performance. No brain response differences were observed during a simple finger-tapping task. The degree of abnormality was greater for teens who reported experiencing more withdrawal or hangover symptoms and who consumed more alcohol. Conclusions: Adolescents with AUD show abnormalities in brain response to a spatial working memory task, despite adequate performance, suggesting that subtle neuronal reorganization may occur early in the course of AUD. [source] Emotional processing in male adolescents with childhood-onset conduct disorderTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 7 2008Sabine C. Herpertz Background:, Boys with early onset of conduct disorder (CD), most of whom also meet diagnostic criteria of a comorbid attention deficit hyperactivity disorder (ADHD), tend to exhibit high levels of aggression throughout development. While a number of functional neuroimaging studies on emotional processing have been performed in antisocial adults, little is known about how CD children process emotional information. Method:, Functional magnetic resonance imaging data were analyzed in 22 male adolescents aged 12 to 17 years with childhood-onset CD (16 of them with comorbid ADHD) compared to 22 age-matched male healthy controls. In order to consider the likely confounding of results through ADHD comorbidity, we performed a supplementary study including 13 adolescent subjects with pure ADHD who were compared with healthy controls. To challenge emotional processing of stimuli, a passive viewing task was applied, presenting pictures of negative, positive or neutral valence. Results:, When comparing CD/combined disorder patients with healthy controls, we found enhanced left-sided amygdala activation in response to negative pictures as compared to neutral pictures in the patient group. In addition, these boys exhibited no reduced activation in the orbitofrontal, anterior cingulate and insular cortices. By contrast, children with pure ADHD did not show any abnormalities in amygdala activation but showed decreased neural activity in the insula only in response to negative pictures. Conclusions:, Increased rather than reduced amygdala activation found in our study may indicate an enhanced response to environmental cues in adolescents with early-onset CD (most of whom also met the condition of ADHD), and is not consistent with the assumption of a reduced capacity to take note of affective information in the social environment. Further studies with an emphasis on developmental aspects of affect regulation are needed to clarify the relationship between CD and adult personality pathology associated with different modes of persistent antisocial behavior. [source] Feasibility of T and Z scores from magnetic resonance imaging data for quantification of cartilage loss in osteoarthritisARTHRITIS & RHEUMATISM, Issue 10 2003R. Burgkart Objective T scores (an indicator of the difference between patients and young healthy subjects) and Z scores (an indicator of the difference between patients and age-matched healthy subjects) are used in the diagnosis of osteoporosis and form the current basis for the definition of osteoporosis by the World Health Organization. We tested the feasibility of using T and Z scores derived from quantitative cartilage imaging with magnetic resonance imaging (MRI) for the diagnosis of osteoarthritis (OA). Methods High-resolution MR images of tibial cartilage were acquired from 126 young healthy adults (ages 20,35 years), 24 age-matched elderly healthy adults (ages 50,75 years), 7 OA patients prior to tibial osteotomy, and 7 OA patients prior to knee arthroplasty. Cartilage volume, thickness, surface area, and original joint surface area (before onset of disease) were determined in the medial and lateral tibia. Results The cartilage volume of the medial tibia of osteotomy patients with varus malalignment displayed moderate T scores (,1.0), and more negative T scores (,3.8) were observed in knee arthroplasty patients with varus malalignment. Normalization of the cartilage volume to the original joint surface area substantially enhanced the scores in patients undergoing osteotomy (,2.3) and in patients undergoing knee arthroplasty (,5.5), and this was superior to the normalization ratios of cartilage volume to body height and cartilage volume to body weight, in terms of distinguishing the loss of articular cartilage. Conclusion Quantitative analysis of OA by MRI is feasible using T and Z scores. However, cartilage volume should be normalized to the individual joint surface area in order to maximize the discriminatory power of this technique for the diagnosis of OA. [source] Flow Distribution During Cardiopulmonary Bypass in Dependency on the Outflow Cannula PositioningARTIFICIAL ORGANS, Issue 11 2009Tim A.S. Kaufmann Abstract Oxygen deficiency in the right brain is a common problem during cardiopulmonary bypass (CPB). This is linked to an insufficient perfusion of the carotid and vertebral artery. The flow to these vessels is strongly influenced by the outflow cannula position, which is traditionally located in the ascending aorta. Another approach however is to return blood via the right subclavian artery. A computational fluid dynamics (CFD) study was performed for both methods and validated by particle image velocimetry (PIV). A 3-dimensional computer aided design model of the cardiovascular (CV) system was generated from realtime computed tomography and magnetic resonance imaging data. Mesh generation (CFD) and rapid prototyping (PIV) were used for the further model creation. The simulations were performed assuming usual CPB conditions, and the same boundary conditions were applied for the PIV validation. The flow distribution was analyzed for 55 cannula positions inside the aorta and in relation to the distance between the cannula tip and the vertebral artery branch for subclavian cannulation. The study reveals that the Venturi effect due to the cannula jet appears to be the main reason for the loss in cerebral perfusion seen clinically. It provides a PIV-validated CFD method of analyzing the flow distribution in the CV system and can be transferred to other applications. [source] On Distance-Based Permutation Tests for Between-Group ComparisonsBIOMETRICS, Issue 2 2010Philip T. Reiss Summary Permutation tests based on distances among multivariate observations have found many applications in the biological sciences. Two major testing frameworks of this kind are multiresponse permutation procedures and pseudo- F,tests arising from a distance-based extension of multivariate analysis of variance. In this article, we derive conditions under which these two frameworks are equivalent. The methods and equivalence results are illustrated by reanalyzing an ecological data set and by a novel application to functional magnetic resonance imaging data. [source] | ||||||||||