A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis
ObjectiveDamage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across mult...
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description | ObjectiveDamage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.Methods442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.ResultsAnalysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.InterpretationThis large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS. |
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The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.Methods442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.ResultsAnalysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.InterpretationThis large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.</description><identifier>ISSN: 0022-3050</identifier><identifier>EISSN: 1468-330X</identifier><identifier>DOI: 10.1136/jnnp-2015-311952</identifier><identifier>PMID: 26746186</identifier><identifier>CODEN: JNNPAU</identifier><language>eng</language><publisher>England: BMJ Publishing Group LTD</publisher><subject>Algorithms ; Alzheimer's disease ; Amyotrophic lateral sclerosis ; Amyotrophic Lateral Sclerosis - diagnostic imaging ; Biomarkers ; Brain - diagnostic imaging ; Cohort Studies ; Datasets ; Dementia ; Diffusion Magnetic Resonance Imaging ; Ethics ; Female ; Humans ; Image Interpretation, Computer-Assisted ; Male ; Middle Aged ; Nerve Net - diagnostic imaging ; Patients ; Prognosis ; Retrospective Studies ; White Matter - diagnostic imaging</subject><ispartof>Journal of neurology, neurosurgery and psychiatry, 2016-06, Vol.87 (6), p.570-579</ispartof><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing</rights><rights>Copyright: 2016 Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b405t-87d391bd871c6c60e53e2e8569769ab4ee9155fe773283c57d1a991a0a7435e43</citedby><cites>FETCH-LOGICAL-b405t-87d391bd871c6c60e53e2e8569769ab4ee9155fe773283c57d1a991a0a7435e43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://jnnp.bmj.com/content/87/6/570.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttps://jnnp.bmj.com/content/87/6/570.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>114,115,314,776,780,3183,23550,27901,27902,77343,77374</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26746186$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Müller, Hans-Peter</creatorcontrib><creatorcontrib>Turner, Martin R</creatorcontrib><creatorcontrib>Grosskreutz, Julian</creatorcontrib><creatorcontrib>Abrahams, Sharon</creatorcontrib><creatorcontrib>Bede, Peter</creatorcontrib><creatorcontrib>Govind, Varan</creatorcontrib><creatorcontrib>Prudlo, Johannes</creatorcontrib><creatorcontrib>Ludolph, Albert C</creatorcontrib><creatorcontrib>Filippi, Massimo</creatorcontrib><creatorcontrib>Kassubek, Jan</creatorcontrib><creatorcontrib>Neuroimaging Society in ALS (NiSALS) DTI Study Group</creatorcontrib><title>A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis</title><title>Journal of neurology, neurosurgery and psychiatry</title><addtitle>J Neurol Neurosurg Psychiatry</addtitle><description>ObjectiveDamage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.Methods442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.ResultsAnalysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.InterpretationThis large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.</description><subject>Algorithms</subject><subject>Alzheimer's disease</subject><subject>Amyotrophic lateral sclerosis</subject><subject>Amyotrophic Lateral Sclerosis - diagnostic imaging</subject><subject>Biomarkers</subject><subject>Brain - diagnostic imaging</subject><subject>Cohort Studies</subject><subject>Datasets</subject><subject>Dementia</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>Ethics</subject><subject>Female</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Nerve Net - diagnostic imaging</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Retrospective Studies</subject><subject>White Matter - diagnostic imaging</subject><issn>0022-3050</issn><issn>1468-330X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkD1LxEAQhhdR9PzorWTBRpDoTjb7VYr4BYKNgl3YbCbnHsnm3E2K-_cmnFrYOM00z_sy8xByCuwKgMvrVQjrLGcgMg5gRL5DFlBInXHO3nfJgrE8zzgT7IAcprRi82izTw5yqQoJWi5IdUNbG5eYJWdbpN3YDt5hGCJShxGraFta-6YZk-8DHTCkPlLf2aUPS5qGsd5QH6jtNv0Q-_WHd1PdgHMquRZjn3w6JnuNbROefO8j8nZ_93r7mD2_PDzd3jxnVcHEkGlVcwNVrRU46SRDwTFHLaRR0tiqQDQgRINK8VxzJ1QN1hiwzKqCCyz4EbnY9q5j_zliGsrOJ4dtawP2YypBacMKDWZGz_-gq36MYbpuogzXKgfQE8W2lJv-SBGbch2n1-OmBFbO_svZfzn7L7f-p8jZd_FYdVj_Bn6ET8DlFqi61f91X6xKjxs</recordid><startdate>201606</startdate><enddate>201606</enddate><creator>Müller, Hans-Peter</creator><creator>Turner, Martin R</creator><creator>Grosskreutz, Julian</creator><creator>Abrahams, Sharon</creator><creator>Bede, Peter</creator><creator>Govind, Varan</creator><creator>Prudlo, Johannes</creator><creator>Ludolph, Albert C</creator><creator>Filippi, Massimo</creator><creator>Kassubek, Jan</creator><general>BMJ Publishing Group LTD</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>201606</creationdate><title>A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis</title><author>Müller, Hans-Peter ; Turner, Martin R ; Grosskreutz, Julian ; Abrahams, Sharon ; Bede, Peter ; Govind, Varan ; Prudlo, Johannes ; Ludolph, Albert C ; Filippi, Massimo ; Kassubek, Jan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b405t-87d391bd871c6c60e53e2e8569769ab4ee9155fe773283c57d1a991a0a7435e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>Alzheimer's disease</topic><topic>Amyotrophic lateral sclerosis</topic><topic>Amyotrophic Lateral Sclerosis - diagnostic imaging</topic><topic>Biomarkers</topic><topic>Brain - diagnostic imaging</topic><topic>Cohort Studies</topic><topic>Datasets</topic><topic>Dementia</topic><topic>Diffusion Magnetic Resonance Imaging</topic><topic>Ethics</topic><topic>Female</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Nerve Net - diagnostic imaging</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Retrospective Studies</topic><topic>White Matter - diagnostic imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Müller, Hans-Peter</creatorcontrib><creatorcontrib>Turner, Martin R</creatorcontrib><creatorcontrib>Grosskreutz, Julian</creatorcontrib><creatorcontrib>Abrahams, Sharon</creatorcontrib><creatorcontrib>Bede, Peter</creatorcontrib><creatorcontrib>Govind, Varan</creatorcontrib><creatorcontrib>Prudlo, Johannes</creatorcontrib><creatorcontrib>Ludolph, Albert C</creatorcontrib><creatorcontrib>Filippi, Massimo</creatorcontrib><creatorcontrib>Kassubek, Jan</creatorcontrib><creatorcontrib>Neuroimaging Society in ALS (NiSALS) DTI Study Group</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>Nursing & Allied Health Database</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>Science Database (Alumni Edition)</collection><collection>STEM Database</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>ProQuest Central</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</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>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Science Database</collection><collection>Nursing & Allied Health Premium</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>MEDLINE - Academic</collection><jtitle>Journal of neurology, neurosurgery and psychiatry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Müller, Hans-Peter</au><au>Turner, Martin R</au><au>Grosskreutz, Julian</au><au>Abrahams, Sharon</au><au>Bede, Peter</au><au>Govind, Varan</au><au>Prudlo, Johannes</au><au>Ludolph, Albert C</au><au>Filippi, Massimo</au><au>Kassubek, Jan</au><aucorp>Neuroimaging Society in ALS (NiSALS) DTI Study Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis</atitle><jtitle>Journal of neurology, neurosurgery and psychiatry</jtitle><addtitle>J Neurol Neurosurg Psychiatry</addtitle><date>2016-06</date><risdate>2016</risdate><volume>87</volume><issue>6</issue><spage>570</spage><epage>579</epage><pages>570-579</pages><issn>0022-3050</issn><eissn>1468-330X</eissn><coden>JNNPAU</coden><abstract>ObjectiveDamage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.Methods442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.ResultsAnalysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.InterpretationThis large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.</abstract><cop>England</cop><pub>BMJ Publishing Group LTD</pub><pmid>26746186</pmid><doi>10.1136/jnnp-2015-311952</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alzheimer's disease Amyotrophic lateral sclerosis Amyotrophic Lateral Sclerosis - diagnostic imaging Biomarkers Brain - diagnostic imaging Cohort Studies Datasets Dementia Diffusion Magnetic Resonance Imaging Ethics Female Humans Image Interpretation, Computer-Assisted Male Middle Aged Nerve Net - diagnostic imaging Patients Prognosis Retrospective Studies White Matter - diagnostic imaging |
title | A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis |
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