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 |
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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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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><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 & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & 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. However, limitations in translation to clinical practice remain.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>29485230</pmid><doi>10.1111/jon.12505</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3160-9022</orcidid><orcidid>https://orcid.org/0000-0002-7792-0433</orcidid></addata></record> |
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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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