A semi-supervised large margin algorithm for white matter hyperintensity segmentation

Precise detection and quantification of white matter hyperintensities (WMH) is of great interest in studies of neurodegenerative diseases (NDs). In this work, we propose a novel semi-supervised large margin algorithm for the segmentation of WMH. The proposed algorithm optimizes a kernel based max-margin objective function which aims to maximize the margin averaged over inliers and outliers while exploiting a limited amount of available labelled data. We show that the learning problem can be formulated as a joint framework learning a classifier and a label assignment simultaneously, which can be solved efficiently by an iterative algorithm. We evaluate our method on a database of 280 brain Magnetic Resonance (MR) images from subjects that either suffered from subjective memory complaints or were diagnosed with NDs. The segmented WMH volumes correlate well with the standard clinical measurement (Fazekas score), and both the qualitative visualization results and quantitative correlation scores of the proposed algorithm outperform other well known methods for WMH segmentation

Gray matter volume reduction in rostral middle frontal gyrus in patients with chronic schizophrenia

The dorsolateral prefrontal cortex (DLPFC) is a brain region that has figured prominently in studies of schizophrenia and working memory, yet the exact neuroanatomical localization of this brain region remains to be defined. DLPFC primarily involves the superior frontal gyrus and middle frontal gyrus (MFG). The latter, however is not a single neuroanatomical entity but instead is comprised of rostral (anterior, middle, and posterior) and caudal regions. In this study we used structural MRI to develop a method for parcellating MFG into its component parts. We focused on this region of DLPFC because it includes BA46, a region involved in working memory. We evaluated volume differences in MFG in 20 patients with chronic schizophrenia and 20 healthy controls. Mid-rostral MFG (MR-MFG) was delineated within the rostral MFG using anterior and posterior neuroanatomical landmarks derived from cytoarchitectonic definitions of BA46. Gray matter volumes of MR-MFG were then compared between groups, and a significant reduction in gray matter volume was observed (p b 0.008), but not in other areas of MFG (i.e., anterior or posterior rostral MFG, or caudal regions of MFG). Our results demonstrate that volumetric alterations in MFG gray matter are localized exclusively to MR-MFG. 3D reconstructions of the cortical surface made it possible to follow MFG into its anterior part, where other approaches have failed. This method of parcellation offers a more precise way of measuring MR-MFG that will likely be important in further documentation of DLPFC anomalies in schizophrenia

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu

Infant Brain Atlases from Neonates to 1- and 2-Year-Olds

Background: Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology: To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-yearold, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between agespecific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions: We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website

Widespread white matter microstructural differences in schizophrenia across 4322 individuals:Results from the ENIGMA Schizophrenia DTI Working Group

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.Molecular Psychiatry advance online publication, 17 October 2017; doi:10.1038/mp.2017.170

The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project

BACKGROUND: Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) Consortium aims to clarify the role of genetic variation in brain abnormalities underlying schizophrenia. This article describes the GENUS Consortium sample collection. METHODS: We identified existing samples collected for schizophrenia studies consisting of patients, controls, and/or individuals at familial high-risk (FHR) for schizophrenia. Samples had single nucleotide polymorphism (SNP) array data or genomic DNA, clinical and demographic data, and neuropsychological and/or brain magnetic resonance imaging (MRI) data. Data were subjected to quality control procedures at a central site. RESULTS: Sixteen research groups contributed data from 5199 psychosis patients, 4877 controls, and 725 FHR individuals. All participants have relevant demographic data and all patients have relevant clinical data. The sex ratio is 56.5% male and 43.5% female. Significant differences exist between diagnostic groups for premorbid and current IQ (both p10,000 participants. The breadth of data across clinical, genetic, neuropsychological, and MRI modalities provides an important opportunity for elucidating the genetic basis of neural processes underlying schizophrenia

Role of RNA secondary structure of the iron-responsive element in translational regulation of ferritin synthesis.

Iron regulates synthesis of the iron storage protein ferritin at the translational level through interaction between a stem-loop structure, the iron-responsive element (IRE), located in the 5'-untranslated region (5'-UTR) of ferritin mRNAs, and a protein, the iron regulatory protein (IRP). The role of IRE secondary structure in translational regulation of ferritin synthesis was explored by introducing ferritin constructs containing mutations in the IRE into Rat-2 fibroblasts. Our in vivo studies demonstrate that size and sequence of the loop within the IRE and the distance and/or spatial relationship of this loop to the bulged nucleotide region closest to the loop must be preserved in order to observe iron-dependent translation of ferritin mRNA. In contrast, changes in nucleotide sequence of the upper stem can be introduced without affecting translational regulation in vivo, as long as a stem can be formed. Our in vivo results suggest that only a very small variation in the affinity of interaction of IRP with IRE can be tolerated in order to maintain iron-dependent regulation of translation