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Alan C Evans

Publications and source records attributed to Alan C Evans.

At least 19 recordsLinked to original sources

Small-world anatomical networks in the human brain revealed by cortical thickness from MRI.

An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.

Brain↗

XXY (Klinefelter syndrome): a pediatric quantitative brain magnetic resonance imaging case-control study.

OBJECTIVE: An extra X chromosome in males (XXY), known as Klinefelter syndrome, is associated with characteristic physical, cognitive, and behavioral features of variable severity. The objective of this study was to examine possible neuroanatomical substrates of these cognitive and behavioral features during childhood and adolescence. METHODS: MRI brain scans were acquired for 42 XXY and 87 healthy XY age-matched control males. We compared these 2 groups on regional brain volumes and cortical thickness. RESULTS: Total cerebral volume and all lobar volumes except parietal white matter were significantly smaller in the XXY group, whereas lateral-ventricle volume was larger. Consistent with the cognitive profile, the cortex was significantly thinner in the XXY group in left inferior frontal, temporal, and superior motor regions. CONCLUSION: The brain-imaging findings of preferentially affected frontal, temporal, and motor regions and relative sparing of parietal regions are consistent with observed cognitive and behavioral strengths and weaknesses in XXY subjects.

Adolescent↗

Focal cortical atrophy in multiple sclerosis: relation to lesion load and disability.

Multiple sclerosis (MS) is thought to predominantly affect white matter (WM). Recently, however, loss of cortical gray matter has also been described. Little is known about the cause of cortical atrophy in MS, whether it occurs early in the disease course, and whether it affects all cortical regions equally or if there is a preferential pattern of focal cortical atrophy. An automated method was used to compute the thickness at every vertex of the cortical surface of the brains of 425 early relapsing-remitting MS patients. We correlated cortical thickness with the WM lesion load and the Expanded Disability Status Scale score. Mean cortical thickness correlated with WM lesion load and disability. The correlations of cortical thickness with total lesion load and disability were most significant in cingulate gyrus, insula, and associative cortical regions. Conversely, primary sensory, visual, and motor areas showed a less significant relationship. The highest amount of atrophy per lesion volume or disability scale unit was in the anterior cingulate cortex. This study confirms the relation between cortical atrophy, WM lesion load, and disability in MS, and suggests that cortical atrophy occurs even in MS patients with only mild disability. Most interestingly, we show a specific regional pattern of focal atrophy in MS that is distinctively different from the one in normal aging. The predilection of the atrophic process for areas that are heavily inter-connected with other brain regions suggests that interruption of WM tracts by MS plaques contributes, at least in part, to the development of cortical atrophy.

Aged↗

Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls.

We investigated the potential of fully automated measurements of cortical thickness to reproduce the clinical diagnosis in Alzheimer's Disease (AD) using 19 patients and 17 healthy controls. Thickness maps were analyzed using three different discriminant techniques to separate patients from controls. All analyses were performed using leave-one-out cross-validation to avoid overtraining of the discriminants. The results show regionally variant patterns of discrimination ability, with over 90% accuracy obtained in the medial temporal lobes and other limbic structures. Multivariate discriminant analysis produced 100% accuracy with six different combinations, all involving the parahippocampal gyrus. We therefore propose automated measurements of cortical thickness as a tool to improve the clinical diagnosis of probable AD, as well as a research method to gain unique insight into the etiology of cortical pathology in the disease.

Aged↗

Genetic contributions to human brain morphology and intelligence.

Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images of 54 monozygotic and 58 dizygotic twin pairs and 34 of their siblings. For genetic analyses, we used structural equation modeling and voxel-based morphometry. To explore the common genetic origin of focal GM and WM areas with intelligence, we obtained cross-trait/cross-twin correlations in which the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0.55). Intelligence shared a common genetic origin with superior occipitofrontal, callosal, and left optical radiation WM and frontal, occipital, and parahippocampal GM (phenotypic correlations up to 0.35). These findings point to a neural network that shares a common genetic origin with human intelligence.

Adolescent↗

Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer's disease.

Cortical thickness is a more reliable measure of atrophy than volume due to the low variability in the cytoarchitectural structure of the grey matter. However, this more desirable measure of disease-related alterations is not fully evaluated in early dementia. The study presented here is the first to report the spatial patterns of cortical thickness in the pre-clinical stages of Alzheimer's disease, namely mild cognitive impairment (MCI). Cortical thickness measurements for 34 healthy elderly, 62 MCI and 42 Alzheimer's disease subjects were made using fully automated magnetic resonance imaging-based analysis techniques in order to determine the pattern of cortical thinning as a function of disease progression. The thickness of the cortex decreased significantly when the healthy elderly brains were compared to those with MCI, mainly in the medial temporal lobe region and in some regions of the frontal and the parietal cortices. With the progression of disease from MCI to Alzheimer's disease, a general thinning of the entire cortex with significant extension into the lateral temporal lobe was found. In all cases, the results were more pronounced in the left hemisphere. In conclusion, we have shown that there is a specific pattern in the thinning of the cortical ribbon which is in agreement with the previous histological reports. These novel findings support the notion of increased isocortical involvement with the progression of disease.

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A new improved version of the realistic digital brain phantom.

Image analysis methods must be tested and evaluated within a controlled environment. Simulations can be an extremely helpful tool for validation because ground truth is known. We created the digital brain phantom that is at the heart of our publicly available database of realistic simulated magnetic resonance image (MRI) volumes known as BrainWeb. Even though the digital phantom had l mm(3) isotropic voxel size and a small number of tissue classes, the BrainWeb database has been used in more than one hundred peer-reviewed publications validating different image processing methods. In this paper, we describe the next step in the natural evolution of BrainWeb: the creation of digital brain phantom II that includes three major improvements over the original phantom. First, the realism of the phantom, and the resulting simulations, was improved by modeling more tissue classes to include blood vessels, bone marrow and dura mater classes. In addition. a more realistic skull class was created. The latter is particularly useful for SPECT, PET and CT simulations for which bone attenuation has an important effect. Second, the phantom was improved by an eight-fold reduction in voxel volume to 0.125 mm(3). Third, the method used to create the new phantom was modified not only to take into account the segmentation of these new structures, but also to take advantage of many more automated procedures now available. The overall process has reduced subjectivity and manual intervention when compared to the original phantom, and the process may be easily applied to create phantoms from other subjects. MRI simulations are shown to illustrate the difference between the previous and the new improved digital brain phantom II. Example PET and SPECT simulations are also presented.

Brain↗

Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI.

We introduce MACACC-Mapping Anatomical Correlations Across Cerebral Cortex-to study correlated changes within and across different cortical networks. The principal topic of investigation is whether the thickness of one area of the cortex changes in a statistically correlated fashion with changes in thickness of other cortical regions. We further extend these methods by introducing techniques to test whether different population groupings exhibit significantly varying MACACC patterns. The methods are described in detail and applied to a normal childhood development population (n = 292), and show that association cortices have the highest correlation strengths. Taking Brodmann Area (BA) 44 as a seed region revealed MACACC patterns strikingly similar to tractography maps obtained from diffusion tensor imaging. Furthermore, the MACACC map of BA 44 changed with age, older subjects featuring tighter correlations with BA 44 in the anterior portions of the superior temporal gyri. Lastly, IQ-dependent MACACC differences were investigated, revealing steeper correlations between BA 44 and multiple frontal and parietal regions for the higher IQ group, most significantly (t = 4.0) in the anterior cingulate.

Adolescent↗

A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom.

Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which represent the true cortical surface in both geometry and topology. However, there has been no explicit comparison study among those methods because each method has its own procedures, file formats, coordinate systems, and use of the reconstructed surface. There has also been no explicit evaluation method except visual inspection to validate the whole-cortical surface models quantitatively. In this study, we presented a novel phantom-based validation method of the cortical surface reconstruction algorithm and quantitatively cross-validated the three most prominent cortical surface reconstruction algorithms which are used in Freesurfer, BrainVISA, and CLASP, respectively. The validation included geometrical accuracy and mesh characteristics such as Euler number, fractal dimension (FD), total surface area, and local density of points. CLASP showed the best geometric/topologic accuracy and mesh characteristics such as FD and total surface area compared to Freesurfer and BrainVISA. In the validation of local density of points, Freesurfer and BrainVISA showed more even distribution of points on the cortical surface compared to CLASP.

Algorithms↗

Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry.

Global gray matter brain tissue volume decreases in schizophrenia have been associated to disease-related (possibly nongenetic) factors. Global white matter brain tissue volume decreases were related to genetic risk factors for the disease. However, which focal gray and white matter brain regions best reflect the genetic and environmental risk factors in the brains of patients with schizophrenia remains unresolved. 1.5-T MRI brain scans of 11 monozygotic and 11 same-sex dizygotic twin-pairs discordant for schizophrenia were compared to 11 monozygotic and 11 same-sex dizygotic healthy control twin-pairs using voxel-based morphometry. Linear regression analysis was done in each voxel for the average and difference in gray and white matter density separately, in each twin-pair, with group (discordant, healthy) and zygosity (monozygotic, dizygotic) as between subject variables, and age, sex and handedness as covariates. The t-maps (critical threshold value mid R:tmid R: > 6.0, P < 0.05) revealed a focal decrease in gray matter density accompanied by a focal increase in white matter density in the left medial orbitofrontal gyrus and a focal decrease in white matter density in the left sensory motor gyrus in twin-pairs discordant for schizophrenia as compared to healthy twin-pairs. Focal changes in left medial (orbito)frontal and left sensory motor gyri may reflect the increased genetic risk to develop schizophrenia. Focal changes in the left anterior hemisphere may therefore be particularly relevant as endophenotype in genetic studies of schizophrenia.

Brain↗

The NIH MRI study of normal brain development.

MRI is increasingly used to study normal and abnormal brain development, but we lack a clear understanding of "normal". Previous studies have been limited by small samples, narrow age ranges and few behavioral measures. This multi-center project conducted epidemiologically based recruitment of a large, demographically balanced sample across a wide age range, using strict exclusion factors and comprehensive clinical/behavioral measures. A mixed cross-sectional and longitudinal design was used to create a MRI/clinical/behavioral database from approximately 500 children aged 7 days to 18 years to be shared with researchers and the clinical medicine community. Using a uniform acquisition protocol, data were collected at six Pediatric Study Centers and consolidated at a Data Coordinating Center. All data were transferred via a web-network into a MYSQL database that allowed (i) secure data transfer, (ii) automated MRI segmentation, (iii) correlation of neuroanatomical and clinical/behavioral variables as 3D statistical maps and (iv) remote interrogation and 3D viewing of database content. A population-based epidemiologic sampling strategy minimizes bias and enhances generalizability of the results. Target accrual tables reflect the demographics of the U.S. population (2000 Census data). Enrolled subjects underwent a standardized protocol to characterize neurobehavioral and pubertal status. All subjects underwent multi-spectral structural MRI. In a subset, we acquired T1/T2 relaxometry, diffusion tensor imaging, single-voxel proton spectroscopy and spectroscopic imaging. In the first of three cycles, successful structural MRI data were acquired in 392 subjects aged 4:6-18:3 years and in 72 subjects aged 7 days to 4:6 years. We describe the methodologies of MRI data acquisition and analysis, using illustrative results. This database will provide a basis for characterizing healthy brain maturation in relationship to behavior and serve as a source of control data for studies of childhood disorders. All data described here will be available to the scientific community from July, 2006.

Adolescent↗

Creation and application of a simulated database of dynamic [18f]MPPF PET acquisitions incorporating inter-individual anatomical and biological variability.

During the process of validation of a new tracer, estimation of performance and validation of processing algorithms have to be investigated with data sets representative of the ground truth. Because this ground truth is hardly accessible in positron emission tomography (PET), validations of processing algorithms often rely on the use of simulated data sets. Considering that Monte Carlo simulators are very time consuming and are not very easy to use, the building of publicly available databases of simulated PET volumes are becoming highly desirable. We present here the methodology employed for the creation of a database of simulated dynamic [18F]MPPF-PET data, including inter-individual anatomical and biological variability which meets the criteria of a gold standard database as defined by Lehmann: reliance, equivalence, independence, relevance, significance. The assessment of the realism of the built database against actual MPPF PET data is also presented here. Whereas the database was specifically created for the investigations of quantification of activity and binding of ligand-receptor with the [18F]MPPF PET tracer, it may serve the community with countless purposes. The full strength of this database, does not only stem from the knowledge of important information such as the true activity map and underlying anatomical data, but also from the possibility to fully control the biological difference between sets of simulated PET data. Indeed, time activity curves included in the simulated data sets are controlled by a multicompartmental model of ligand-receptor exchanges. This latter feature is of a great interest in the context of the improvement of the detectability of biological variation in PET.

Brain↗

Twenty new digital brain phantoms for creation of validation image data bases.

Simulations provide a way of generating data where ground truth is known, enabling quantitative testing of image processing methods. In this paper, we present the construction of 20 realistic digital brain phantoms that can be used to simulate medical imaging data. The phantoms are made from 20 normal adults to take into account intersubject anatomical variabilities. Each digital brain phantom was created by registering and averaging four T1, T2, and proton density (PD)-weighted magnetic resonance imaging (MRI) scans from each subject. A fuzzy minimum distance classification was used to classify voxel intensities from T1, T2, and PD average volumes into grey-matter, white matter, cerebro-spinal fluid, and fat. Automatically generated mask volumes were required to separate brain from nonbrain structures and ten fuzzy tissue volumes were created: grey matter, white matter, cerebro-spinal fluid, skull, marrow within the bone, dura, fat, tissue around the fat, muscles, and skin/muscles. A fuzzy vessel class was also obtained from the segmentation of the magnetic resonance angiography scan of the subject. These eleven fuzzy volumes that describe the spatial distribution of anatomical tissues define the digital phantom, where voxel intensity is proportional to the fraction of tissue within the voxel. These fuzzy volumes can be used to drive simulators for different modalities including MRI, PET, or SPECT. These phantoms were used to construct 20 simulated T1-weighted MR scans. To evaluate the realism of these simulations, we propose two approaches to compare them to real data acquired with the same acquisition parameters. The first approach consists of comparing the intensities within the segmented classes in both real and simulated data. In the second approach, a whole brain voxel-wise comparison between simulations and real T1-weighted data is performed. The first comparison underlines that segmented classes appear to properly represent the anatomy on average, and that inside these classes, the simulated and real intensity values are quite similar. The second comparison enables the study of the regional variations with no a priori class. The experiments demonstrate that these variations are small when real data are corrected for intensity nonuniformity.

Adult↗

Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification.

Accurate reconstruction of the inner and outer cortical surfaces of the human cerebrum is a critical objective for a wide variety of neuroimaging analysis purposes, including visualization, morphometry, and brain mapping. The Anatomic Segmentation using Proximity (ASP) algorithm, previously developed by our group, provides a topology-preserving cortical surface deformation method that has been extensively used for the aforementioned purposes. However, constraints in the algorithm to ensure topology preservation occasionally produce incorrect thickness measurements due to a restriction in the range of allowable distances between the gray and white matter surfaces. This problem is particularly prominent in pediatric brain images with tightly folded gyri. This paper presents a novel method for improving the conventional ASP algorithm by making use of partial volume information through probabilistic classification in order to allow for topology preservation across a less restricted range of cortical thickness values. The new algorithm also corrects the classification of the insular cortex by masking out subcortical tissues. For 70 pediatric brains, validation experiments for the modified algorithm, Constrained Laplacian ASP (CLASP), were performed by three methods: (i) volume matching between surface-masked gray matter (GM) and conventional tissue-classified GM, (ii) surface matching between simulated and CLASP-extracted surfaces, and (iii) repeatability of the surface reconstruction among 16 MRI scans of the same subject. In the volume-based evaluation, the volume enclosed by the CLASP WM and GM surfaces matched the classified GM volume 13% more accurately than using conventional ASP. In the surface-based evaluation, using synthesized thick cortex, the average difference between simulated and extracted surfaces was 4.6 +/- 1.4 mm for conventional ASP and 0.5 +/- 0.4 mm for CLASP. In a repeatability study, CLASP produced a 30% lower RMS error for the GM surface and a 8% lower RMS error for the WM surface compared with ASP.

Algorithms↗

Comparing functional connectivity via thresholding correlations and singular value decomposition.

We compare two common methods for detecting functional connectivity: thresholding correlations and singular value decomposition (SVD). We find that thresholding correlations are better at detecting focal regions of correlated voxels, whereas SVD is better at detecting extensive regions of correlated voxels. We apply these results to resting state networks in an fMRI dataset to look for connectivity in cortical thickness.

Brain↗

Cortical thickness analysis in autism with heat kernel smoothing.

We present a novel data smoothing and analysis framework for cortical thickness data defined on the brain cortical manifold. Gaussian kernel smoothing, which weights neighboring observations according to their 3D Euclidean distance, has been widely used in 3D brain images to increase the signal-to-noise ratio. When the observations lie on a convoluted brain surface, however, it is more natural to assign the weights based on the geodesic distance along the surface. We therefore develop a framework for geodesic distance-based kernel smoothing and statistical analysis on the cortical manifolds. As an illustration, we apply our methods in detecting the regions of abnormal cortical thickness in 16 high functioning autistic children via random field based multiple comparison correction that utilizes the new smoothing technique.

Adolescent↗

Cortical thickness analysis examined through power analysis and a population simulation.

We have previously developed a procedure for measuring the thickness of cerebral cortex over the whole brain using 3-D MRI data and a fully automated surface-extraction (ASP) algorithm. This paper examines the precision of this algorithm, its optimal performance parameters, and the sensitivity of the method to subtle, focal changes in cortical thickness. The precision of cortical thickness measurements was studied using a simulated population study and single subject reproducibility metrics. Cortical thickness was shown to be a reliable method, reaching a sensitivity (probability of a true-positive) of 0.93. Six different cortical thickness metrics were compared. The simplest and most precise method measures the distance between corresponding vertices from the white matter to the gray matter surface. Given two groups of 25 subjects, a 0.6-mm (15%) change in thickness can be recovered after blurring with a 3-D Gaussian kernel (full-width half max = 30 mm). Smoothing across the 2-D surface manifold also improves precision; in this experiment, the optimal kernel size was 30 mm.

Algorithms↗

Correlation of cerebrospinal fluid levels of tau protein phosphorylated at threonine 231 with rates of hippocampal atrophy in Alzheimer disease.

BACKGROUND: The microtubule-associated tau protein abnormally phosphorylated at threonine 231 (p-tau231) has been investigated as a potential marker of Alzheimer disease. Levels of cerebrospinal fluid (CSF) p-tau231 vary across patients with Alzheimer disease. We hypothesized that these variations partially reflect differences in the degree of neuronal damage and therefore may be used to predict structural disease progression. OBJECTIVE: To investigate whether CSF p-tau231 levels correlate with rates of hippocampal atrophy as an in vivo marker of regional neuronal loss. DESIGN AND PATIENTS: We measured hippocampal volumes on the basis of serial magnetic resonance image examinations in 22 patients with Alzheimer disease. In addition, we determined CSF p-tau231 levels at baseline. RESULTS: Levels of CSF p-tau231 were significantly correlated with baseline hippocampal volumes (P<.001) and rates of hippocampal atrophy (left hippocampus, P<.001; right hippocampus, P = .02), independent of disease duration and severity. CONCLUSION: These findings suggest that variations in p-tau231 levels may be used to predict progression of brain atrophy in patients with Alzheimer disease.

Aged↗