| Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome. | |
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MedLine Citation:
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PMID: 22281673 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. |
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Authors:
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Dafnis Batalle; Elisenda Eixarch; Francesc Figueras; Emma Muñoz-Moreno; Nuria Bargallo; Miriam Illa; Ruthy Acosta-Rojas; Ivan Amat-Roldan; Eduard Gratacos |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-1-18 |
Journal Detail:
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Title: NeuroImage Volume: - ISSN: 1095-9572 ISO Abbreviation: - Publication Date: 2012 Jan |
Date Detail:
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Created Date: 2012-1-27 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9215515 Medline TA: Neuroimage Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2012. Published by Elsevier Inc. |
Affiliation:
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Department of Maternal-Fetal Medicine, Institut Clínic de Ginecologia, Obstetrícia i Neonatologia (ICGON), Hospital Clínic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Sabino de Arana 1, 08028 Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain. |
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