One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI?
White matter microstructural changes during the first three years of healthy brain development are characterized using two different models developed for limited clinical diffusion data: White Matter Tract Integrity (WMTI) metrics from Diffusional Kurtosis Imaging (DKI) and Neurite Orientation Dispe...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2015-02, Vol.107, p.242-256 |
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| creator | Jelescu, Ileana O Veraart, Jelle Adisetiyo, Vitria Milla, Sarah S Novikov, Dmitry S Fieremans, Els |
| description | White matter microstructural changes during the first three years of healthy brain development are characterized using two different models developed for limited clinical diffusion data: White Matter Tract Integrity (WMTI) metrics from Diffusional Kurtosis Imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI). Both models reveal a non-linear increase in intra-axonal water fraction and in tortuosity of the extra-axonal space as a function of age, in the genu and splenium of the corpus callosum and the posterior limb of the internal capsule. The changes are consistent with expected behavior related to myelination and asynchrony of fiber development. The intra- and extracellular axial diffusivities as estimated with WMTI do not change appreciably in normal brain development. The quantitative differences in parameter estimates between models are examined and explained in the light of each model's assumptions and consequent biases, as highlighted in simulations. Finally, we discuss the feasibility of a model with fewer assumptions. |
| doi_str_mv | 10.1016/j.neuroimage.2014.12.009 |
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Both models reveal a non-linear increase in intra-axonal water fraction and in tortuosity of the extra-axonal space as a function of age, in the genu and splenium of the corpus callosum and the posterior limb of the internal capsule. The changes are consistent with expected behavior related to myelination and asynchrony of fiber development. The intra- and extracellular axial diffusivities as estimated with WMTI do not change appreciably in normal brain development. The quantitative differences in parameter estimates between models are examined and explained in the light of each model's assumptions and consequent biases, as highlighted in simulations. Finally, we discuss the feasibility of a model with fewer assumptions.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2014.12.009</identifier><identifier>PMID: 25498427</identifier><language>eng</language><publisher>United States: Elsevier Limited</publisher><subject>Age ; Aging - physiology ; Axons - physiology ; Computer Simulation ; Corpus callosum ; Corpus Callosum - growth & development ; Corpus Callosum - physiology ; Diffusion ; Diffusion Magnetic Resonance Imaging ; Female ; Humans ; Infant ; Infant, Newborn ; Internal Capsule - growth & development ; Internal Capsule - physiology ; Kurtosis ; Male ; Microstructure ; Models, Neurological ; Myelin Sheath - physiology ; Myelination ; Nerve Fibers, Myelinated - physiology ; Neurites - physiology ; Neuroimaging ; Newborn babies ; Substantia alba ; White Matter - anatomy & histology ; White Matter - growth & development</subject><ispartof>NeuroImage (Orlando, Fla.), 2015-02, Vol.107, p.242-256</ispartof><rights>Copyright © 2013 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Feb 15, 2015</rights><rights>2014 Elsevier Inc. All rights reserved. 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c575t-794166ea8c16debd6f0b8db0a7a3141f93e7cd0b9c86c3ab94c8ace1836957593</citedby><cites>FETCH-LOGICAL-c575t-794166ea8c16debd6f0b8db0a7a3141f93e7cd0b9c86c3ab94c8ace1836957593</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1645696067?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,780,784,885,27923,27924,64384,64386,64388,72240</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25498427$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jelescu, Ileana O</creatorcontrib><creatorcontrib>Veraart, Jelle</creatorcontrib><creatorcontrib>Adisetiyo, Vitria</creatorcontrib><creatorcontrib>Milla, Sarah S</creatorcontrib><creatorcontrib>Novikov, Dmitry S</creatorcontrib><creatorcontrib>Fieremans, Els</creatorcontrib><title>One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI?</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>White matter microstructural changes during the first three years of healthy brain development are characterized using two different models developed for limited clinical diffusion data: White Matter Tract Integrity (WMTI) metrics from Diffusional Kurtosis Imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI). Both models reveal a non-linear increase in intra-axonal water fraction and in tortuosity of the extra-axonal space as a function of age, in the genu and splenium of the corpus callosum and the posterior limb of the internal capsule. The changes are consistent with expected behavior related to myelination and asynchrony of fiber development. The intra- and extracellular axial diffusivities as estimated with WMTI do not change appreciably in normal brain development. The quantitative differences in parameter estimates between models are examined and explained in the light of each model's assumptions and consequent biases, as highlighted in simulations. Finally, we discuss the feasibility of a model with fewer assumptions.</description><subject>Age</subject><subject>Aging - physiology</subject><subject>Axons - physiology</subject><subject>Computer Simulation</subject><subject>Corpus callosum</subject><subject>Corpus Callosum - growth & development</subject><subject>Corpus Callosum - physiology</subject><subject>Diffusion</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>Female</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Internal Capsule - growth & development</subject><subject>Internal Capsule - physiology</subject><subject>Kurtosis</subject><subject>Male</subject><subject>Microstructure</subject><subject>Models, Neurological</subject><subject>Myelin Sheath - physiology</subject><subject>Myelination</subject><subject>Nerve Fibers, Myelinated - physiology</subject><subject>Neurites - physiology</subject><subject>Neuroimaging</subject><subject>Newborn babies</subject><subject>Substantia alba</subject><subject>White Matter - 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physiology</topic><topic>Axons - physiology</topic><topic>Computer Simulation</topic><topic>Corpus callosum</topic><topic>Corpus Callosum - growth & development</topic><topic>Corpus Callosum - physiology</topic><topic>Diffusion</topic><topic>Diffusion Magnetic Resonance Imaging</topic><topic>Female</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Internal Capsule - growth & development</topic><topic>Internal Capsule - physiology</topic><topic>Kurtosis</topic><topic>Male</topic><topic>Microstructure</topic><topic>Models, Neurological</topic><topic>Myelin Sheath - physiology</topic><topic>Myelination</topic><topic>Nerve Fibers, Myelinated - physiology</topic><topic>Neurites - physiology</topic><topic>Neuroimaging</topic><topic>Newborn babies</topic><topic>Substantia alba</topic><topic>White Matter - anatomy & histology</topic><topic>White Matter - growth & development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jelescu, Ileana O</creatorcontrib><creatorcontrib>Veraart, Jelle</creatorcontrib><creatorcontrib>Adisetiyo, Vitria</creatorcontrib><creatorcontrib>Milla, Sarah S</creatorcontrib><creatorcontrib>Novikov, Dmitry S</creatorcontrib><creatorcontrib>Fieremans, Els</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jelescu, Ileana O</au><au>Veraart, Jelle</au><au>Adisetiyo, Vitria</au><au>Milla, Sarah S</au><au>Novikov, Dmitry S</au><au>Fieremans, Els</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI?</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2015-02-15</date><risdate>2015</risdate><volume>107</volume><spage>242</spage><epage>256</epage><pages>242-256</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>White matter microstructural changes during the first three years of healthy brain development are characterized using two different models developed for limited clinical diffusion data: White Matter Tract Integrity (WMTI) metrics from Diffusional Kurtosis Imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI). Both models reveal a non-linear increase in intra-axonal water fraction and in tortuosity of the extra-axonal space as a function of age, in the genu and splenium of the corpus callosum and the posterior limb of the internal capsule. The changes are consistent with expected behavior related to myelination and asynchrony of fiber development. The intra- and extracellular axial diffusivities as estimated with WMTI do not change appreciably in normal brain development. The quantitative differences in parameter estimates between models are examined and explained in the light of each model's assumptions and consequent biases, as highlighted in simulations. Finally, we discuss the feasibility of a model with fewer assumptions.</abstract><cop>United States</cop><pub>Elsevier Limited</pub><pmid>25498427</pmid><doi>10.1016/j.neuroimage.2014.12.009</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; ScienceDirect Journals (5 years ago - present); ProQuest Central UK/Ireland |
| subjects | Age Aging - physiology Axons - physiology Computer Simulation Corpus callosum Corpus Callosum - growth & development Corpus Callosum - physiology Diffusion Diffusion Magnetic Resonance Imaging Female Humans Infant Infant, Newborn Internal Capsule - growth & development Internal Capsule - physiology Kurtosis Male Microstructure Models, Neurological Myelin Sheath - physiology Myelination Nerve Fibers, Myelinated - physiology Neurites - physiology Neuroimaging Newborn babies Substantia alba White Matter - anatomy & histology White Matter - growth & development |
| title | One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI? |
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