A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms
Objective To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. Methods W...
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Veröffentlicht in: | Annals of neurology 2016-10, Vol.80 (4), p.581-592 |
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creator | Baykara, Ebru Gesierich, Benno Adam, Ruth Tuladhar, Anil Man Biesbroek, J. Matthijs Koek, Huiberdina L. Ropele, Stefan Jouvent, Eric Chabriat, Hugues Ertl-Wagner, Birgit Ewers, Michael Schmidt, Reinhold de Leeuw, Frank-Erik Biessels, Geert Jan Dichgans, Martin Duering, Marco |
description | Objective
To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.
Methods
We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.
Results
PSMD was associated with processing speed in all study samples with SVD (p‐values between 2.8 × 10−3 and 1.8 × 10−10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.
Interpretation
PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581–592. |
doi_str_mv | 10.1002/ana.24758 |
format | Article |
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To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.
Methods
We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.
Results
PSMD was associated with processing speed in all study samples with SVD (p‐values between 2.8 × 10−3 and 1.8 × 10−10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.
Interpretation
PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581–592.</description><identifier>ISSN: 0364-5134</identifier><identifier>EISSN: 1531-8249</identifier><identifier>DOI: 10.1002/ana.24758</identifier><identifier>PMID: 27518166</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Alzheimer Disease - diagnostic imaging ; Biomarkers ; Cerebral Small Vessel Diseases - complications ; Cerebral Small Vessel Diseases - diagnostic imaging ; Cognitive Dysfunction - diagnostic imaging ; Cognitive Dysfunction - etiology ; Cognitive Dysfunction - physiopathology ; Diffusion Tensor Imaging - methods ; Diffusion Tensor Imaging - standards ; Female ; Humans ; Male ; Middle Aged ; Reproducibility of Results ; White Matter - diagnostic imaging ; Young Adult</subject><ispartof>Annals of neurology, 2016-10, Vol.80 (4), p.581-592</ispartof><rights>2016 American Neurological Association</rights><rights>2016 American Neurological Association.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4908-4c67cf96d498aca3b2ffe081db01f4b7e5de8de3425393a1192eeb10b5ea33773</citedby><cites>FETCH-LOGICAL-c4908-4c67cf96d498aca3b2ffe081db01f4b7e5de8de3425393a1192eeb10b5ea33773</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fana.24758$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fana.24758$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27518166$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Baykara, Ebru</creatorcontrib><creatorcontrib>Gesierich, Benno</creatorcontrib><creatorcontrib>Adam, Ruth</creatorcontrib><creatorcontrib>Tuladhar, Anil Man</creatorcontrib><creatorcontrib>Biesbroek, J. Matthijs</creatorcontrib><creatorcontrib>Koek, Huiberdina L.</creatorcontrib><creatorcontrib>Ropele, Stefan</creatorcontrib><creatorcontrib>Jouvent, Eric</creatorcontrib><creatorcontrib>Chabriat, Hugues</creatorcontrib><creatorcontrib>Ertl-Wagner, Birgit</creatorcontrib><creatorcontrib>Ewers, Michael</creatorcontrib><creatorcontrib>Schmidt, Reinhold</creatorcontrib><creatorcontrib>de Leeuw, Frank-Erik</creatorcontrib><creatorcontrib>Biessels, Geert Jan</creatorcontrib><creatorcontrib>Dichgans, Martin</creatorcontrib><creatorcontrib>Duering, Marco</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><title>A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms</title><title>Annals of neurology</title><addtitle>Ann Neurol</addtitle><description>Objective
To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.
Methods
We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.
Results
PSMD was associated with processing speed in all study samples with SVD (p‐values between 2.8 × 10−3 and 1.8 × 10−10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.
Interpretation
PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581–592.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alzheimer Disease - diagnostic imaging</subject><subject>Biomarkers</subject><subject>Cerebral Small Vessel Diseases - complications</subject><subject>Cerebral Small Vessel Diseases - diagnostic imaging</subject><subject>Cognitive Dysfunction - diagnostic imaging</subject><subject>Cognitive Dysfunction - etiology</subject><subject>Cognitive Dysfunction - physiopathology</subject><subject>Diffusion Tensor Imaging - methods</subject><subject>Diffusion Tensor Imaging - standards</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Reproducibility of Results</subject><subject>White Matter - diagnostic imaging</subject><subject>Young Adult</subject><issn>0364-5134</issn><issn>1531-8249</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkU9PFDEYhxujkQU9-AVMEy96GOjfaXtcQIFkXQ_gcmw6M2_XgZkptDMCfnq7LnAwMfHSN837_J6k_SH0jpJ9Sgg7cIPbZ0JJ_QLNqOS00EyYl2hGeCkKSbnYQbspXRFCTEnJa7TDlKSaluUM3c_xMvyEDp_1bt0Oa_zVxWuI2IeIz3vXdXgFKeX9cZvAJcCH-WhwGPD5NXQwhqH95cY234PHlz_aEbJhHLPhIrp6TNgNTc56P6UNdNqmMayj69Mb9Mq7LsHbx7mHvn_5fHF0Wiy-nZwdzRdFLQzRhahLVXtTNsJoVzteMe-BaNpUhHpRKZAN6Aa4YJIb7ig1DKCipJLgOFeK76GPW-9NDLcTpNH2baqh69wAYUqWaqa0kYzw_0GFFMIIltEPf6FXYYpDfsiG4lpqYjbUpy1Vx5BSBG9vYtu7-GApsZvmbG7O_mkus-8fjVPVQ_NMPlWVgYMtcNd28PBvk50v50_KYpvInw73z4lcsC0VV9JeLk_sSvLD1bEUdsF_A3VisIA</recordid><startdate>201610</startdate><enddate>201610</enddate><creator>Baykara, Ebru</creator><creator>Gesierich, Benno</creator><creator>Adam, Ruth</creator><creator>Tuladhar, Anil Man</creator><creator>Biesbroek, J. Matthijs</creator><creator>Koek, Huiberdina L.</creator><creator>Ropele, Stefan</creator><creator>Jouvent, Eric</creator><creator>Chabriat, Hugues</creator><creator>Ertl-Wagner, Birgit</creator><creator>Ewers, Michael</creator><creator>Schmidt, Reinhold</creator><creator>de Leeuw, Frank-Erik</creator><creator>Biessels, Geert Jan</creator><creator>Dichgans, Martin</creator><creator>Duering, Marco</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><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>7TK</scope><scope>7U7</scope><scope>C1K</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>201610</creationdate><title>A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms</title><author>Baykara, Ebru ; Gesierich, Benno ; Adam, Ruth ; Tuladhar, Anil Man ; Biesbroek, J. Matthijs ; Koek, Huiberdina L. ; Ropele, Stefan ; Jouvent, Eric ; Chabriat, Hugues ; Ertl-Wagner, Birgit ; Ewers, Michael ; Schmidt, Reinhold ; de Leeuw, Frank-Erik ; Biessels, Geert Jan ; Dichgans, Martin ; Duering, Marco</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4908-4c67cf96d498aca3b2ffe081db01f4b7e5de8de3425393a1192eeb10b5ea33773</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Alzheimer Disease - diagnostic imaging</topic><topic>Biomarkers</topic><topic>Cerebral Small Vessel Diseases - complications</topic><topic>Cerebral Small Vessel Diseases - diagnostic imaging</topic><topic>Cognitive Dysfunction - diagnostic imaging</topic><topic>Cognitive Dysfunction - etiology</topic><topic>Cognitive Dysfunction - physiopathology</topic><topic>Diffusion Tensor Imaging - methods</topic><topic>Diffusion Tensor Imaging - standards</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Reproducibility of Results</topic><topic>White Matter - diagnostic imaging</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Baykara, Ebru</creatorcontrib><creatorcontrib>Gesierich, Benno</creatorcontrib><creatorcontrib>Adam, Ruth</creatorcontrib><creatorcontrib>Tuladhar, Anil Man</creatorcontrib><creatorcontrib>Biesbroek, J. Matthijs</creatorcontrib><creatorcontrib>Koek, Huiberdina L.</creatorcontrib><creatorcontrib>Ropele, Stefan</creatorcontrib><creatorcontrib>Jouvent, Eric</creatorcontrib><creatorcontrib>Chabriat, Hugues</creatorcontrib><creatorcontrib>Ertl-Wagner, Birgit</creatorcontrib><creatorcontrib>Ewers, Michael</creatorcontrib><creatorcontrib>Schmidt, Reinhold</creatorcontrib><creatorcontrib>de Leeuw, Frank-Erik</creatorcontrib><creatorcontrib>Biessels, Geert Jan</creatorcontrib><creatorcontrib>Dichgans, Martin</creatorcontrib><creatorcontrib>Duering, Marco</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Annals of neurology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Baykara, Ebru</au><au>Gesierich, Benno</au><au>Adam, Ruth</au><au>Tuladhar, Anil Man</au><au>Biesbroek, J. Matthijs</au><au>Koek, Huiberdina L.</au><au>Ropele, Stefan</au><au>Jouvent, Eric</au><au>Chabriat, Hugues</au><au>Ertl-Wagner, Birgit</au><au>Ewers, Michael</au><au>Schmidt, Reinhold</au><au>de Leeuw, Frank-Erik</au><au>Biessels, Geert Jan</au><au>Dichgans, Martin</au><au>Duering, Marco</au><aucorp>Alzheimer's Disease Neuroimaging Initiative</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms</atitle><jtitle>Annals of neurology</jtitle><addtitle>Ann Neurol</addtitle><date>2016-10</date><risdate>2016</risdate><volume>80</volume><issue>4</issue><spage>581</spage><epage>592</epage><pages>581-592</pages><issn>0364-5134</issn><eissn>1531-8249</eissn><abstract>Objective
To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.
Methods
We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.
Results
PSMD was associated with processing speed in all study samples with SVD (p‐values between 2.8 × 10−3 and 1.8 × 10−10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.
Interpretation
PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581–592.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>27518166</pmid><doi>10.1002/ana.24758</doi><tpages>12</tpages></addata></record> |
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subjects | Adult Aged Aged, 80 and over Alzheimer Disease - diagnostic imaging Biomarkers Cerebral Small Vessel Diseases - complications Cerebral Small Vessel Diseases - diagnostic imaging Cognitive Dysfunction - diagnostic imaging Cognitive Dysfunction - etiology Cognitive Dysfunction - physiopathology Diffusion Tensor Imaging - methods Diffusion Tensor Imaging - standards Female Humans Male Middle Aged Reproducibility of Results White Matter - diagnostic imaging Young Adult |
title | A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms |
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