Literature DB >> 30450154

ESTIMATION OF SHAPE AND GROWTH BRAIN NETWORK ATLASES FOR CONNECTOMIC BRAIN MAPPING IN DEVELOPING INFANTS.

Islem Rekik1,2, Gang Li2, Weili Lin2, Dinggang Shen2.   

Abstract

In vivo brain connectomics have heavily relied on using functional and diffusion Magnetic Resonance Imaging (MRI) modalities to examine functional and structural relationships between pairs of anatomical regions in the brain. However, research work on brain morphological (i.e., shape-to-shape) connections, which can be derived from T1-w and T2-w MR images, in both typical and atypical development or ageing is very scarce. Furthermore, the brain cannot be only regarded as a static shape, since it is a dynamic complex system that changes at functional, structural and morphological levels. Hence, examining the 'connection' between brain shape and its changes with time (e.g., growth) may help advance our understanding of connectomic brain dynamics as well as disorders that may affect it. To address these limitations, we unprecedentedly introduce two population-based shape and growth connectivity analysis tools that further extend the field of connectomics to brain morphology and dynamics: the morphome and the kinectome. Specifically, for a population of anatomically labelled shapes, the morphome identifies a network of anatomical shape regions that are connected when morphologically similar at a single timepoint, whereas the kinectome identifies anatomical shape regions that elicit similar evolution dynamics across successive timepoints. These proposed generic tools can be easily invested to examine how a baseline shape influences its deformation trajectory at later timepoints using any longitudinal shape data. We evaluated these tools on 23 infants, with right and left cortical surfaces reconstructed at birth, 3, 6, 9 and 12 months of age. Investigating the relationship between the neonatal morphome and the postnatal kinectome (from birth to 1 year of age) gave insights into brain connectivity at birth and how it develops over time.

Entities:  

Keywords:  Brain Connectivity; Cortex Morphology; Growth and Shape; Kinetcome; Morphome; Shape Similarity Networks

Year:  2018        PMID: 30450154      PMCID: PMC6239168          DOI: 10.1109/ISBI.2018.8363736

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  17 in total

1.  Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?

Authors:  Herve Lemaitre; Aaron L Goldman; Fabio Sambataro; Beth A Verchinski; Andreas Meyer-Lindenberg; Daniel R Weinberger; Venkata S Mattay
Journal:  Neurobiol Aging       Date:  2010-08-23       Impact factor: 4.673

2.  Age-related temporal and parietal cortical thinning in autism spectrum disorders.

Authors:  Gregory L Wallace; Nathan Dankner; Lauren Kenworthy; Jay N Giedd; Alex Martin
Journal:  Brain       Date:  2010-10-05       Impact factor: 13.501

Review 3.  Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms.

Authors:  Michael I Miller
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

4.  Age-Related Cortical Thickness Reduction in Non-Demented Down's Syndrome Subjects.

Authors:  Andrea Romano; Riccardo Cornia; Marta Moraschi; Alessandro Bozzao; Laura Chiacchiararelli; Valeria Coppola; Cristina Iani; Giacomo Stella; Giorgio Albertini; Alberto Pierallini
Journal:  J Neuroimaging       Date:  2015-05-21       Impact factor: 2.486

5.  Hippocampal atrophy and ventricular enlargement in normal aging, mild cognitive impairment (MCI), and Alzheimer Disease.

Authors:  Liana G Apostolova; Amity E Green; Sona Babakchanian; Kristy S Hwang; Yi-Yu Chou; Arthur W Toga; Paul M Thompson
Journal:  Alzheimer Dis Assoc Disord       Date:  2012 Jan-Mar       Impact factor: 2.703

6.  Asymmetries of cortical shape: Effects of handedness, sex and schizophrenia.

Authors:  Katherine L Narr; Robert M Bilder; Eileen Luders; Paul M Thompson; Roger P Woods; Delbert Robinson; Philip R Szeszko; Teodora Dimtcheva; Mala Gurbani; Arthur W Toga
Journal:  Neuroimage       Date:  2006-12-12       Impact factor: 6.556

7.  Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

Authors:  Islem Rekik; Gang Li; Weili Lin; Dinggang Shen
Journal:  Med Image Anal       Date:  2015-11-10       Impact factor: 8.545

8.  Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces.

Authors:  Gang Li; Jingxin Nie; Li Wang; Feng Shi; John H Gilmore; Weili Lin; Dinggang Shen
Journal:  Neuroimage       Date:  2013-12-27       Impact factor: 6.556

9.  Multimodal population brain imaging in the UK Biobank prospective epidemiological study.

Authors:  Karla L Miller; Fidel Alfaro-Almagro; Neal K Bangerter; David L Thomas; Essa Yacoub; Junqian Xu; Andreas J Bartsch; Saad Jbabdi; Stamatios N Sotiropoulos; Jesper L R Andersson; Ludovica Griffanti; Gwenaëlle Douaud; Thomas W Okell; Peter Weale; Iulius Dragonu; Steve Garratt; Sarah Hudson; Rory Collins; Mark Jenkinson; Paul M Matthews; Stephen M Smith
Journal:  Nat Neurosci       Date:  2016-09-19       Impact factor: 24.884

10.  Heritability of the shape of subcortical brain structures in the general population.

Authors:  Gennady V Roshchupkin; Boris A Gutman; Meike W Vernooij; Neda Jahanshad; Nicholas G Martin; Albert Hofman; Katie L McMahon; Sven J van der Lee; Cornelia M van Duijn; Greig I de Zubicaray; André G Uitterlinden; Margaret J Wright; Wiro J Niessen; Paul M Thompson; M Arfan Ikram; Hieab H H Adams
Journal:  Nat Commun       Date:  2016-12-15       Impact factor: 14.919

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