The Role of High‐Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis

ABSTRACT BACKGROUND AND PURPOSE A relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investig...

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Veröffentlicht in:Journal of neuroimaging 2018-05, Vol.28 (3), p.328-337
Hauptverfasser: Uher, Tomas, Krasensky, Jan, Sobisek, Lukas, Seidl, Zdenek, Bergsland, Niels, Dwyer, Michael G., Kubala Havrdova, Eva, Zivadinov, Robert, Horakova, Dana, Vaneckova, Manuela
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container_end_page 337
container_issue 3
container_start_page 328
container_title Journal of neuroimaging
container_volume 28
creator Uher, Tomas
Krasensky, Jan
Sobisek, Lukas
Seidl, Zdenek
Bergsland, Niels
Dwyer, Michael G.
Kubala Havrdova, Eva
Zivadinov, Robert
Horakova, Dana
Vaneckova, Manuela
description ABSTRACT BACKGROUND AND PURPOSE A relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investigate if high‐frequency brain MRI monitoring affects identification of pathological BVL in an individual patient. METHODS One hundred fifty‐seven relapsing‐remitting MS patients had seven MRI scans over 12 months follow‐up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time‐points. RESULTS An analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time‐points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time‐points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time‐points was 14.7%. CONCLUSIONS High‐frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. However, limitations in translation to clinical practice remain.
doi_str_mv 10.1111/jon.12505
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Objective of this study was to investigate if high‐frequency brain MRI monitoring affects identification of pathological BVL in an individual patient. METHODS One hundred fifty‐seven relapsing‐remitting MS patients had seven MRI scans over 12 months follow‐up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time‐points. RESULTS An analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time‐points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time‐points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time‐points was 14.7%. CONCLUSIONS High‐frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. However, limitations in translation to clinical practice remain.</description><identifier>ISSN: 1051-2284</identifier><identifier>EISSN: 1552-6569</identifier><identifier>DOI: 10.1111/jon.12505</identifier><identifier>PMID: 29485230</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Atrophy ; Brain ; brain atrophy ; high‐frequency MRI ; individual patient ; Magnetic resonance imaging ; Monitoring ; Multiple sclerosis ; Neuroimaging ; NMR ; Nuclear magnetic resonance ; Patients ; precision ; Regression analysis ; Volumetric analysis</subject><ispartof>Journal of neuroimaging, 2018-05, Vol.28 (3), p.328-337</ispartof><rights>Copyright © 2018 by the American Society of Neuroimaging</rights><rights>Copyright © 2018 by the American Society of Neuroimaging.</rights><rights>Copyright © 2018 American Society of Neuroimaging</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3535-209b57e48e938593c7866b7dd3a45dc321fc6e904e2a47b1e596b4f9dcc4c17c3</citedby><cites>FETCH-LOGICAL-c3535-209b57e48e938593c7866b7dd3a45dc321fc6e904e2a47b1e596b4f9dcc4c17c3</cites><orcidid>0000-0003-3160-9022 ; 0000-0002-7792-0433</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjon.12505$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjon.12505$$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/29485230$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Uher, Tomas</creatorcontrib><creatorcontrib>Krasensky, Jan</creatorcontrib><creatorcontrib>Sobisek, Lukas</creatorcontrib><creatorcontrib>Seidl, Zdenek</creatorcontrib><creatorcontrib>Bergsland, Niels</creatorcontrib><creatorcontrib>Dwyer, Michael G.</creatorcontrib><creatorcontrib>Kubala Havrdova, Eva</creatorcontrib><creatorcontrib>Zivadinov, Robert</creatorcontrib><creatorcontrib>Horakova, Dana</creatorcontrib><creatorcontrib>Vaneckova, Manuela</creatorcontrib><title>The Role of High‐Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis</title><title>Journal of neuroimaging</title><addtitle>J Neuroimaging</addtitle><description>ABSTRACT BACKGROUND AND PURPOSE A relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investigate if high‐frequency brain MRI monitoring affects identification of pathological BVL in an individual patient. METHODS One hundred fifty‐seven relapsing‐remitting MS patients had seven MRI scans over 12 months follow‐up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time‐points. RESULTS An analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time‐points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time‐points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time‐points was 14.7%. CONCLUSIONS High‐frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. However, limitations in translation to clinical practice remain.</description><subject>Atrophy</subject><subject>Brain</subject><subject>brain atrophy</subject><subject>high‐frequency MRI</subject><subject>individual patient</subject><subject>Magnetic resonance imaging</subject><subject>Monitoring</subject><subject>Multiple sclerosis</subject><subject>Neuroimaging</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Patients</subject><subject>precision</subject><subject>Regression analysis</subject><subject>Volumetric analysis</subject><issn>1051-2284</issn><issn>1552-6569</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp10MlOwzAQBmALgdgPvACKxAUOAa-JfYSyi4LEco4SZ0JdpXaxE6HeeASekSfBpcABCV9sWd_8mhmEdgg-JPEcjZ09JFRgsYTWiRA0zUSmluMbC5JSKvka2ghhjDElnLJVtEYVl4IyvI704wiSe9dC4prk0jyPPt7ezz289GD1LBneXyVDZ03nvLHPibFJF_kpdKA74-y85sSX8fu48246ms3FsG87M42BD7oF74IJW2ilKdsA29_3Jno6P3scXKY3dxdXg-ObVDPBREqxqkQOXIJiUiimc5llVV7XrOSi1oySRmegMAda8rwiIFRW8UbVWnNNcs020f4id-pdHCB0xcQEDW1bWnB9KCjGUirCuIx07w8du97b2F1UjGUyV4pGdbBQOs4RPDTF1JtJ6WcFwcV887HKFl-bj3b3O7GvJlD_yp9VR3C0AK-mhdn_ScX13e0i8hMgSYx6</recordid><startdate>201805</startdate><enddate>201805</enddate><creator>Uher, Tomas</creator><creator>Krasensky, Jan</creator><creator>Sobisek, Lukas</creator><creator>Seidl, Zdenek</creator><creator>Bergsland, Niels</creator><creator>Dwyer, Michael G.</creator><creator>Kubala Havrdova, Eva</creator><creator>Zivadinov, Robert</creator><creator>Horakova, Dana</creator><creator>Vaneckova, Manuela</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3160-9022</orcidid><orcidid>https://orcid.org/0000-0002-7792-0433</orcidid></search><sort><creationdate>201805</creationdate><title>The Role of High‐Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis</title><author>Uher, Tomas ; Krasensky, Jan ; Sobisek, Lukas ; Seidl, Zdenek ; Bergsland, Niels ; Dwyer, Michael G. ; Kubala Havrdova, Eva ; Zivadinov, Robert ; Horakova, Dana ; Vaneckova, Manuela</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3535-209b57e48e938593c7866b7dd3a45dc321fc6e904e2a47b1e596b4f9dcc4c17c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Atrophy</topic><topic>Brain</topic><topic>brain atrophy</topic><topic>high‐frequency MRI</topic><topic>individual patient</topic><topic>Magnetic resonance imaging</topic><topic>Monitoring</topic><topic>Multiple sclerosis</topic><topic>Neuroimaging</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Patients</topic><topic>precision</topic><topic>Regression analysis</topic><topic>Volumetric analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Uher, Tomas</creatorcontrib><creatorcontrib>Krasensky, Jan</creatorcontrib><creatorcontrib>Sobisek, Lukas</creatorcontrib><creatorcontrib>Seidl, Zdenek</creatorcontrib><creatorcontrib>Bergsland, Niels</creatorcontrib><creatorcontrib>Dwyer, Michael G.</creatorcontrib><creatorcontrib>Kubala Havrdova, Eva</creatorcontrib><creatorcontrib>Zivadinov, Robert</creatorcontrib><creatorcontrib>Horakova, Dana</creatorcontrib><creatorcontrib>Vaneckova, Manuela</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of neuroimaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Uher, Tomas</au><au>Krasensky, Jan</au><au>Sobisek, Lukas</au><au>Seidl, Zdenek</au><au>Bergsland, Niels</au><au>Dwyer, Michael G.</au><au>Kubala Havrdova, Eva</au><au>Zivadinov, Robert</au><au>Horakova, Dana</au><au>Vaneckova, Manuela</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Role of High‐Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis</atitle><jtitle>Journal of neuroimaging</jtitle><addtitle>J Neuroimaging</addtitle><date>2018-05</date><risdate>2018</risdate><volume>28</volume><issue>3</issue><spage>328</spage><epage>337</epage><pages>328-337</pages><issn>1051-2284</issn><eissn>1552-6569</eissn><abstract>ABSTRACT BACKGROUND AND PURPOSE A relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investigate if high‐frequency brain MRI monitoring affects identification of pathological BVL in an individual patient. METHODS One hundred fifty‐seven relapsing‐remitting MS patients had seven MRI scans over 12 months follow‐up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time‐points. RESULTS An analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time‐points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time‐points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time‐points was 14.7%. CONCLUSIONS High‐frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. 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source Wiley Online Library Journals Frontfile Complete
subjects Atrophy
Brain
brain atrophy
high‐frequency MRI
individual patient
Magnetic resonance imaging
Monitoring
Multiple sclerosis
Neuroimaging
NMR
Nuclear magnetic resonance
Patients
precision
Regression analysis
Volumetric analysis
title The Role of High‐Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis
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