Individual parcellation of resting fMRI with a group functional connectivity prior.

Cortical parcellation based on resting fMRI is an important tool for investigating the functional organization and connectivity of the cerebral cortex. Group parcellation based on co-registration of anatomical images to a common atlas will inevitably result in errors in the locations of the boundaries of functional parcels when they are mapped back from the atlas to the individual. This is because areas of functional specialization vary across individuals in a manner that cannot be fully determined from the sulcal and gyral anatomy that is used for mapping between atlas and individual. We describe a method that avoids this problem by refining an initial group parcellation so that for each subject the parcel boundaries are optimized with respect to that subject's resting fMRI. Initialization with a common parcellation results in automatic correspondence between parcels across subjects. Further, by using a group sparsity constraint to model connectivity, we exploit group similarities in connectivity between parcels while optimizing their boundaries for each individual. We applied this approach with initialization on both high and low density group cortical parcellations and used resting fMRI data to refine across a group of individuals. Cross validation studies show improved homogeneity of resting activity within the refined parcels. Comparisons with task-based localizers show consistent reduction of variance of statistical parametric maps within the refined parcels relative to the group-based initialization indicating improved delineation of regions of functional specialization. This method enables a more accurate estimation of individual subject functional areas, facilitating group analysis of functional connectivity, while maintaining consistency across individuals with a standardized topological atlas.

Side-Effects and Social Norms Influencing Family Planning Use in Nepal.

Background Effective family planning (FP) programs promote modern contraceptives and help individuals achieve their reproductive goals. Despite Nepal's relatively high contraceptive prevalence rate (50%), 27% of married women have an unmet need for FP, and almost half of Nepalese women give birth by the age of 20. This formative study explored the factors that influence the use of contraceptives in Nepal. Objective To provide information about barriers to family planning use, general fertility awareness, and barriers to family planning use among difficult to reach groups communities. Method This qualitative study was implemented in five districts in Nepal. A total of 36 focus group discussions, 18 participatory group discussions, and 144 in-depth interviews were conducted. Participants included young married women, men and FP service providers in eight village development committees and two municipalities. The interviews were digitally recorded, transcribed in Nepali and then translated into English. Data was organized using Atlas Ti 7 and coded using a thematic analysis. Result Four key themes emerged from the analyses: 1) limited knowledge on fertility awareness and family planning methods, 2) religious-cultural factors including social norms impediments contraceptives use, 3) fear of side-effects, myths and misconceptions about modern contraceptives, and 4) structural barriers such as limited family planning services, and lack of same gender providers make it difficult for many women to access modern contraceptives services. Conclusion Continuing Nepal's recent gains in contraceptives prevalence rate will require strong educational interventions addressing fertility awareness, social norms around son preference, dispelling fear of side-effects while increasing the family planning method-mix. Health service providers should continue counseling clients on the management of potential side-effects and ensure accurate information about modern contraceptives.

Automated MRI Volumetric Analysis in Patients with Rasmussen Syndrome.

BACKGROUND AND PURPOSE: Rasmussen syndrome, also known as Rasmussen encephalitis, is typically associated with volume loss of the affected hemisphere of the brain. Our aim was to apply automated quantitative volumetric MR imaging analyses to patients diagnosed with Rasmussen encephalitis, to determine the predictive value of lobar volumetric measures and to assess regional atrophy differences as well as monitor disease progression by using these measures. MATERIALS AND METHODS: Nineteen patients (42 scans) with diagnosed Rasmussen encephalitis were studied. We used 2 control groups: one with 42 age- and sex-matched healthy subjects and the other with 42 epileptic patients without Rasmussen encephalitis with the same disease duration as patients with Rasmussen encephalitis. Volumetric analysis was performed on T1-weighted images by using BrainSuite. Ratios of volumes from the affected hemisphere divided by those from the unaffected hemisphere were used as input to a logistic regression classifier, which was trained to discriminate patients from controls. Using the classifier, we compared the predictive accuracy of all the volumetric measures. These ratios were used to further assess regional atrophy differences and correlate with epilepsy duration. RESULTS: Interhemispheric and frontal lobe ratios had the best prediction accuracy for separating patients with Rasmussen encephalitis from healthy controls and patient controls without Rasmussen encephalitis. The insula showed significantly more atrophy compared with all the other cortical regions. Patients with longitudinal scans showed progressive volume loss in the affected hemisphere. Atrophy of the frontal lobe and insula correlated significantly with epilepsy duration. CONCLUSIONS: Automated quantitative volumetric analysis provides accurate separation of patients with Rasmussen encephalitis from healthy controls and epileptic patients without Rasmussen encephalitis, and thus may assist the diagnosis of Rasmussen encephalitis. Volumetric analysis could also be included as part of follow-up for patients with Rasmussen encephalitis to assess disease progression.

An invariant shape representation using the anisotropic Helmholtz equation.

Analyzing geometry of sulcal curves on the human cortical surface requires a shape representation invariant to Euclidean motion. We present a novel shape representation that characterizes the shape of a curve in terms of a coordinate system based on the eigensystem of the anisotropic Helmholtz equation. This representation has many desirable properties: stability, uniqueness and invariance to scaling and isometric transformation. Under this representation, we can find a point-wise shape distance between curves as well as a bijective smooth point-to-point correspondence. When the curves are sampled irregularly, we also present a fast and accurate computational method for solving the eigensystem using a finite element formulation. This shape representation is used to find symmetries between corresponding sulcal shapes between cortical hemispheres. For this purpose, we automatically generate 26 sulcal curves for 24 subject brains and then compute their invariant shape representation. Left-right sulcal shape symmetry as measured by the shape representation's metric demonstrates the utility of the presented invariant representation for shape analysis of the cortical folding pattern.

Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression.

The HTR1A -1019C>G genotype was associated with major depression in the Utah population. Linkage analysis on Utah pedigrees with strong family histories of major depression including only cases with the HTR1A -1019G allele revealed a linkage peak on chromosome 10 (maximum HLOD=4.4). Sequencing of all known genes in the linkage region revealed disease-segregating single-nucleotide polymorphisms (SNPs) in LHPP. LHPP SNPs were also associated with major depression in both Utah and Ashkenazi populations. Consistent with the linkage evidence, LHPP associations depended on HTR1A genotype. Lhpp or a product of a collinear brain-specific transcript, therefore, may interact with Htr1a in the pathogenesis of major depression.

POSTURE MATCHING AND ELASTIC REGISTRATION OF A MOUSE ATLAS TO SURFACE TOPOGRAPHY RANGE DATA.

Estimation of internal mouse anatomy is required for quantitative bioluminescence or fluorescence tomography. However, only surface range data can be recovered from all-optical systems. These data are at times sparse or incomplete. We present a method for fitting an elastically deformable mouse atlas to surface topographic range data acquired by an optical system. In this method, we first match the postures of a deformable atlas and the range data of the mouse being imaged. This is achieved by aligning manually identified landmarks. We then minimize the asymmetric L(2) pseudo-distance between the surface of the deformable atlas and the surface topography range data. Once this registration is accomplished, the internal anatomy of the atlas is transformed to the coordinate system of the range data using elastic energy minimization. We evaluated our method by using it to register a digital mouse atlas to a surface model produced from a manually labeled CT mouse data set. Dice coefficents indicated excellent agreement in the brain and heart, with fair agreement in the kidneys and bladder. We also present example results produced using our method to align the digital mouse atlas to surface range data.

LRIG1 negatively regulates the oncogenic EGF receptor mutant EGFRvIII.

Epidermal growth factor receptor (EGFR) mutation is frequently observed in human cancer and contributes to the growth, survival and therapeutic resistance of tumors. EGFRvIII is an oncogenic EGFR mutant resulting from the deletion of exons 2-7 and is the most common EGFR mutant observed in glioblastoma multiforme, an aggressive brain tumor. EGFRvIII is constitutively active but poorly ubiquitinated, leading to inefficient receptor trafficking to lysosomes and unattenuated oncogenic signaling. The mechanism by which EGFRvIII evades downregulation is not fully understood although recent studies suggest that its interaction with the ubiquitin ligase Cbl may be compromised. In this study, we examine the regulation of EGFRvIII by the recently identified negative regulator, LRIG1, which targets EGFR through recognition of its extracellular domain. Here, we determine whether the extracellular domain deletion in EGFRvIII renders it refractory to LRIG1 regulation. We find that EGFRvIII retains interaction with LRIG1 and is in fact more sensitive to LRIG1 action than wild-type receptor. We demonstrate that LRIG1 regulation of EGFRvIII is distinct from the only other known mechanism of EGFR regulation, Cbl-mediated degradation. Ectopic expression of LRIG1 in EGFRvIII(+) glioblastoma cells opposes EGFRvIII-driven tumor cell proliferation, survival, motility and invasion. Finally, RNAi-mediated silencing of LRIG1 alters EGFRvIII intracellular trafficking and leads to enhanced EGFRvIII expression, suggesting that loss of LRIG1 in tumors may contribute to a permissive environment for EGFRvIII overexpression, contributing to EGFRvIII oncogenesis.

Diffusion tensor MRI shows abnormal brainstem crossing fibers associated with ROBO3 mutations.

Horizontal gaze palsy with progressive scoliosis (HGPPS) is caused by mutations in the ROBO3 gene, critical for the crossing of long ascending medial lemniscal and descending corticospinal tracts in the medulla. Diffusion tensor imaging in a patient with HGGPS revealed the absence of major pontine crossing fiber tracts and no decussation of the superior cerebellar peduncles. Mutations in the ROBO3 gene lead to a widespread lack of crossing fibers throughout the brainstem.

Variants in Apaf-1 segregating with major depression promote apoptosome function.

APAF1, encoding the protein apoptosis protease activating factor 1 (Apaf-1), has recently been established as a chromosome 12 gene conferring predisposition to major depression in humans. The molecular phenotypes of Apaf-1 variants were determined by in vitro reconstruction of the apoptosome complex in which Apaf-1 activates caspase 9 and thus initiates a cascade of proteolytic events leading to apoptotic destruction of the cell. Cellular phenotypes were measured using a yeast heterologous expression assay in which human Apaf-1 and other proteins necessary to constitute a functional apoptotic pathway were overexpressed. Apaf-1 variants encoded by APAF1 alleles that segregate with major depression in families linked to chromosome 12 shared a common gain-of-function phenotype in both assay systems. In contrast, other Apaf-1 variants showed neutral or loss-of-function phenotypes. The depression-associated alleles thus have a common phenotype that is distinct from that of non-associated variants. This result suggests an etiologic role for enhanced apoptosis in major depression.

The human cerebral cortex on MRI: value of the coronal plane.

The evaluation of different cortical areas of the cerebral cortex has been analyzed using MRI of 50 normal subjects without any neurological symptoms. This analysis has been made with different spin echo and gradient echo in T1 or T2 in three different planes: horizontal, sagittal and coronal. The most accurate plane to define important cortical areas such as Broca area, Wernicke area, temporal cortex at the level of the superior temporal sulcus, angular gyrus, supra marginal gyrus, hippocampal and parahippocampal cortices as well as that of the parieto or temporo-occipital areas is the coronal plane. Evidently it must be correlated with the other orthogonal planes. To be compared with the main Atlas of Neuroanatomy these sections must be perpendicular or parallel to the plane passing through the anterior and posterior commissures. MRI of patients with neurological disorders must have, as a routine, a series of MR sections performed in the coronal plane, as well as in horizontal and sagittal ones. The coronal plane is certainly the most precise to evaluate these areas involved in language, memory, visuo spatial or behavioral functions. It must be always compared with the rest of the neuroradiological examination and correlated with the clinical neurological signs.

Analysis of the brain-stem white-matter tracts with diffusion tensor imaging.

The authors have reviewed the diffusion tensor imaging (DTI) of the brain stem in 19 subjects, consisting of 15 normal volunteers and four multi-system atrophy patients. The study was performed with 1.5 T MRI scanners. DTI was correlated with an automated program allowing superposition of the structural anatomy. Axial, sagittal, and coronal images demonstrated major white-matter fibers within the brain stem, including cortico-spinal tracts, transverse pontine fibers, and medial lemniscus. Smaller fibers, such as medial longitudinal fascicles and central tegmental tracts are difficult to visualize. To identify the anatomical orientation of the brain stem, white-matter fibers will help us understand the different functional disease processes, and DTI will play an important role for the evaluation of the different white matter fibers in the brain stem.

Analysis of missense variation in human BRCA1 in the context of interspecific sequence variation.

INTRODUCTION: Interpretation of results from mutation screening of tumour suppressor genes known to harbour high risk susceptibility mutations, such as APC, BRCA1, BRCA2, MLH1, MSH2, TP53, and PTEN, is becoming an increasingly important part of clinical practice. Interpretation of truncating mutations, gene rearrangements, and obvious splice junction mutations, is generally straightforward. However, classification of missense variants often presents a difficult problem. From a series of 20,000 full sequence tests of BRCA1 carried out at Myriad Genetic Laboratories, a total of 314 different missense changes and eight in-frame deletions were observed. Before this study, only 21 of these missense changes were classified as deleterious or suspected deleterious and 14 as neutral or of little clinical significance. METHODS: We have used a combination of a multiple sequence alignment of orthologous BRCA1 sequences and a measure of the chemical difference between the amino acids present at individual residues in the sequence alignment to classify missense variants and in-frame deletions detected during mutation screening of BRCA1. RESULTS: In the present analysis we were able to classify an additional 50 missense variants and two in-frame deletions as probably deleterious and 92 missense variants as probably neutral. Thus we have tentatively classified about 50% of the unclassified missense variants observed during clinical testing of BRCA1. DISCUSSION: An internal test of the analysis is consistent with our classification of the variants designated probably deleterious; however, we must stress that this classification is tentative and does not have sufficient independent confirmation to serve as a clinically applicable stand alone method.

Internet2-based 3D PET image reconstruction using a PC cluster.

We describe an approach to fast iterative reconstruction from fully three-dimensional (3D) PET data using a network of PentiumIII PCs configured as a Beowulf cluster. To facilitate the use of this system, we have developed a browser-based interface using Java. The system compresses PET data on the user's machine, sends these data over a network, and instructs the PC cluster to reconstruct the image. The cluster implements a parallelized version of our preconditioned conjugate gradient method for fully 3D MAP image reconstruction. We report on the speed-up factors using the Beowulf approach and the impacts of communication latencies in the local cluster network and the network connection between the user's machine and our PC cluster.

Linkage of body mass index to chromosome 20 in Utah pedigrees.

Several linkage studies have hinted at the existence of an obesity predisposition locus on chromosome 20, but none of these studies has produced conclusive results. Therefore, we analyzed 48 genetic markers on chromosome 20 for linkage to severe obesity (BMI> or =35) in 103 extended Utah pedigrees (1,711 individuals), all of which had strong aggregation of severe obesity. A simple dominant model produced a maximum multipoint heterogeneity LOD score of 3.5 at D20S438 (55.1 cM). Two additional analyses were performed. First, a one-gene, two-mutation model (with one dominant mutation and one recessive mutation) increased the LOD score to 4.2. Second, a two-locus model (with one locus dominant and one recessive) generated a multipoint LOD score of 4.9. We conclude that one or more severe obesity predisposing genes lie within an interval of approx. 10 cM on chromosome 20. This study generated significant LOD scores which confirm suggestive linkage reports from previous studies. In addition, our analyses suggest that the predisposing gene(s) is localized very near the chromosome 20 centromere.

Automated graph-based analysis and correction of cortical volume topology.

The human cerebral cortex is topologically equivalent to a sheet and can be considered topologically spherical if it is closed at the brain stem. Low-level segmentation of magnetic resonance (MR) imagery typically produces cerebral volumes whose tessellations are not topologically spherical. We present a novel algorithm that analyzes and constrains the topology of a volumetric object. Graphs are formed that represent the connectivity of voxel segments in the foreground and background of the image. These graphs are analyzed and minimal corrections to the volume are made prior to tessellation. We apply the algorithm to a simple test object and to cerebral white matter masks generated by a low-level tissue identification sequence. We tessellate the resulting objects using the marching cubes algorithm and verify their topology by computing their Euler characteristics. A key benefit of the algorithm is that it localizes the change to a volume to the specific areas of its topological defects.

Magnetic resonance image tissue classification using a partial volume model.

We describe a sequence of low-level operations to isolate and classify brain tissue within T1-weighted magnetic resonance images (MRI). Our method first removes nonbrain tissue using a combination of anisotropic diffusion filtering, edge detection, and mathematical morphology. We compensate for image nonuniformities due to magnetic field inhomogeneities by fitting a tricubic B-spline gain field to local estimates of the image nonuniformity spaced throughout the MRI volume. The local estimates are computed by fitting a partial volume tissue measurement model to histograms of neighborhoods about each estimate point. The measurement model uses mean tissue intensity and noise variance values computed from the global image and a multiplicative bias parameter that is estimated for each region during the histogram fit. Voxels in the intensity-normalized image are then classified into six tissue types using a maximum a posteriori classifier. This classifier combines the partial volume tissue measurement model with a Gibbs prior that models the spatial properties of the brain. We validate each stage of our algorithm on real and phantom data. Using data from the 20 normal MRI brain data sets of the Internet Brain Segmentation Repository, our method achieved average kappa indices of kappa = 0.746 +/- 0.114 for gray matter (GM) and kappa = 0.798 +/- 0.089 for white matter (WM) compared to expert labeled data. Our method achieved average kappa indices kappa = 0.893 +/- 0.041 for GM and kappa = 0.928 +/- 0.039 for WM compared to the ground truth labeling on 12 volumes from the Montreal Neurological Institute's BrainWeb phantom.