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Quantitative diffusion weighted imaging measures in patients with multiple sclerosis
Diffusion-weighted imaging (DWI) has been proposed as a sensitive measure of disease severity capable of detecting subtle changes in gray matter and white matter brain compartments in patients with multiple sclerosis (MS). However, DWI has been applied to the study of MS clinical subtypes in only a...
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| Published in: | NeuroImage (Orlando, Fla.) Fla.), 2007-07, Vol.36 (3), p.746-754 |
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| creator | Tavazzi, Eleonora Dwyer, Michael G. Weinstock-Guttman, Bianca Lema, Jordan Bastianello, Stefano Bergamaschi, Roberto Cosi, Vittorio Benedict, Ralph H.B. Munschauer, Frederick E. Zivadinov, Robert |
| description | Diffusion-weighted imaging (DWI) has been proposed as a sensitive measure of disease severity capable of detecting subtle changes in gray matter and white matter brain compartments in patients with multiple sclerosis (MS). However, DWI has been applied to the study of MS clinical subtypes in only a few studies. The objective of this study was to demonstrate the validity of a novel, fully automated method for the calculation of quantitative DWI measures. We also wanted to assess the correlation between whole brain (WB)-DWI variables and clinical and MRI measures of disease severity in a large cohort of MS patients. For this purpose we studied 432 consecutive MS patients (mean age 44.4±10.2 years), 16 patients with clinically isolated syndrome (CIS) and 38 normal controls (NC) using 1.5 T brain MRI. Clinical disease subtypes were as follows: 294 relapsing–remitting (RR), 123 secondary-progressive (SP) and 15 primary-progressive (PP). Mean disease duration was 12±10 years. Mean Expanded Disability Status Scale (EDSS) was 3.3±2.1. Brain parenchymal fraction (BPF), gray matter fraction (GMF) and white matter fraction (WMF) were calculated using a fully automated method. Mean parenchymal diffusivity (MPD) maps were created. DWI indices of peak position (PP), peak height (PH), MPD and entropy (ENT) were obtained. T2- and T1-lesion volumes (LV), EDSS, ambulation index (AI) and nine-hole peg test (9-HPT) were also assessed. MS patients had significantly lower BPF (d=1.26; p |
| doi_str_mv | 10.1016/j.neuroimage.2007.03.056 |
| format | article |
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However, DWI has been applied to the study of MS clinical subtypes in only a few studies. The objective of this study was to demonstrate the validity of a novel, fully automated method for the calculation of quantitative DWI measures. We also wanted to assess the correlation between whole brain (WB)-DWI variables and clinical and MRI measures of disease severity in a large cohort of MS patients. For this purpose we studied 432 consecutive MS patients (mean age 44.4±10.2 years), 16 patients with clinically isolated syndrome (CIS) and 38 normal controls (NC) using 1.5 T brain MRI. Clinical disease subtypes were as follows: 294 relapsing–remitting (RR), 123 secondary-progressive (SP) and 15 primary-progressive (PP). Mean disease duration was 12±10 years. Mean Expanded Disability Status Scale (EDSS) was 3.3±2.1. Brain parenchymal fraction (BPF), gray matter fraction (GMF) and white matter fraction (WMF) were calculated using a fully automated method. Mean parenchymal diffusivity (MPD) maps were created. DWI indices of peak position (PP), peak height (PH), MPD and entropy (ENT) were obtained. T2- and T1-lesion volumes (LV), EDSS, ambulation index (AI) and nine-hole peg test (9-HPT) were also assessed. MS patients had significantly lower BPF (d=1.26; p<0.001) and GMF (d=0.61; p=0.003), and higher ENT (d=1.2; p<0.0001), MPD (d=1.04; p<0.0001) and PH (d=0.47; p=0.045) than NC subjects. A GLM analysis, adjusted for age and multiple comparisons, revealed significant differences between different clinical subtypes for BPF, GMF, ENT, PH, PP, T2-LV and T1-LV (p<0.0001), WMF (p=0.001) and MPD (p=0.023). In RR and SP MS patients, ENT showed a more robust correlation with other MRI (r=0.54 to 0.67, p<0.0001) and clinical (r=0.31 to 0.36, p<0.0001) variables than MPD (r=0.23 to 0.41, p<0.001 for MRI and r=0.13 to 0.18; p=0.006 to p<0.001 for clinical variables). The GMF and BPF showed a slightly stronger relationship with all clinical variables (r=0.33 to 0.48; p<0.0001), when compared to both lesion and DWI measures. ENT (R2=0.28; p<0.0001) and GMF (R2=0.26; p<0.001) were best related with SP disease course. This study highlights the validity of DWI in discerning differences between NC and MS patients, as well as between different MS subtypes. ENT is a sensitive marker of overall brain damage that is strongly related to clinical impairment in patients with SP MS.]]></description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2007.03.056</identifier><identifier>PMID: 17498974</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adolescent ; Adult ; Aged ; Automation ; Brain - pathology ; Brain atrophy ; Clinical disability ; Cohort Studies ; Diffusion ; Diffusion imaging ; Diffusion Magnetic Resonance Imaging ; Entropy ; Female ; Humans ; Image Processing, Computer-Assisted ; Lesion volume ; Male ; Mean diffusivity ; Middle Aged ; MRI ; Multiple sclerosis ; Multiple Sclerosis - classification ; Multiple Sclerosis - pathology ; Neurologic Examination ; Neuropsychological Tests ; Pathology ; Prospective Studies ; Studies</subject><ispartof>NeuroImage (Orlando, Fla.), 2007-07, Vol.36 (3), p.746-754</ispartof><rights>2007 Elsevier Inc.</rights><rights>Copyright Elsevier Limited Jul 1, 2007</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-f4a95fd5f0d2103a6683743e5aa9a48db206d9bfa73371091be7968d1713e4da3</citedby><cites>FETCH-LOGICAL-c400t-f4a95fd5f0d2103a6683743e5aa9a48db206d9bfa73371091be7968d1713e4da3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17498974$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tavazzi, Eleonora</creatorcontrib><creatorcontrib>Dwyer, Michael G.</creatorcontrib><creatorcontrib>Weinstock-Guttman, Bianca</creatorcontrib><creatorcontrib>Lema, Jordan</creatorcontrib><creatorcontrib>Bastianello, Stefano</creatorcontrib><creatorcontrib>Bergamaschi, Roberto</creatorcontrib><creatorcontrib>Cosi, Vittorio</creatorcontrib><creatorcontrib>Benedict, Ralph H.B.</creatorcontrib><creatorcontrib>Munschauer, Frederick E.</creatorcontrib><creatorcontrib>Zivadinov, Robert</creatorcontrib><title>Quantitative diffusion weighted imaging measures in patients with multiple sclerosis</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description><![CDATA[Diffusion-weighted imaging (DWI) has been proposed as a sensitive measure of disease severity capable of detecting subtle changes in gray matter and white matter brain compartments in patients with multiple sclerosis (MS). However, DWI has been applied to the study of MS clinical subtypes in only a few studies. The objective of this study was to demonstrate the validity of a novel, fully automated method for the calculation of quantitative DWI measures. We also wanted to assess the correlation between whole brain (WB)-DWI variables and clinical and MRI measures of disease severity in a large cohort of MS patients. For this purpose we studied 432 consecutive MS patients (mean age 44.4±10.2 years), 16 patients with clinically isolated syndrome (CIS) and 38 normal controls (NC) using 1.5 T brain MRI. Clinical disease subtypes were as follows: 294 relapsing–remitting (RR), 123 secondary-progressive (SP) and 15 primary-progressive (PP). Mean disease duration was 12±10 years. Mean Expanded Disability Status Scale (EDSS) was 3.3±2.1. Brain parenchymal fraction (BPF), gray matter fraction (GMF) and white matter fraction (WMF) were calculated using a fully automated method. Mean parenchymal diffusivity (MPD) maps were created. DWI indices of peak position (PP), peak height (PH), MPD and entropy (ENT) were obtained. T2- and T1-lesion volumes (LV), EDSS, ambulation index (AI) and nine-hole peg test (9-HPT) were also assessed. MS patients had significantly lower BPF (d=1.26; p<0.001) and GMF (d=0.61; p=0.003), and higher ENT (d=1.2; p<0.0001), MPD (d=1.04; p<0.0001) and PH (d=0.47; p=0.045) than NC subjects. A GLM analysis, adjusted for age and multiple comparisons, revealed significant differences between different clinical subtypes for BPF, GMF, ENT, PH, PP, T2-LV and T1-LV (p<0.0001), WMF (p=0.001) and MPD (p=0.023). In RR and SP MS patients, ENT showed a more robust correlation with other MRI (r=0.54 to 0.67, p<0.0001) and clinical (r=0.31 to 0.36, p<0.0001) variables than MPD (r=0.23 to 0.41, p<0.001 for MRI and r=0.13 to 0.18; p=0.006 to p<0.001 for clinical variables). The GMF and BPF showed a slightly stronger relationship with all clinical variables (r=0.33 to 0.48; p<0.0001), when compared to both lesion and DWI measures. ENT (R2=0.28; p<0.0001) and GMF (R2=0.26; p<0.001) were best related with SP disease course. This study highlights the validity of DWI in discerning differences between NC and MS patients, as well as between different MS subtypes. ENT is a sensitive marker of overall brain damage that is strongly related to clinical impairment in patients with SP MS.]]></description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Automation</subject><subject>Brain - pathology</subject><subject>Brain atrophy</subject><subject>Clinical disability</subject><subject>Cohort Studies</subject><subject>Diffusion</subject><subject>Diffusion imaging</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>Entropy</subject><subject>Female</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Lesion volume</subject><subject>Male</subject><subject>Mean diffusivity</subject><subject>Middle Aged</subject><subject>MRI</subject><subject>Multiple sclerosis</subject><subject>Multiple Sclerosis - classification</subject><subject>Multiple Sclerosis - pathology</subject><subject>Neurologic Examination</subject><subject>Neuropsychological Tests</subject><subject>Pathology</subject><subject>Prospective Studies</subject><subject>Studies</subject><issn>1053-8119</issn><issn>1095-9572</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNqFkE1r3DAQhkVo6G6T_oUgKPRmZ2RZlnVslyYNBEogOQutNd5o8cdWHxv67yuzC4FeehodntE770MIZVAyYM3tvpww-dmNZodlBSBL4CWI5oKsGShRKCGrD8tb8KJlTK3IpxD2AKBY3X4kKyZr1SpZr8nzUzJTdNFEd0RqXd-n4OaJvqHbvUa0dMlw046OaELyGKib6CHTOMVA31x8pWMaojsMSEM3oJ-DC9fksjdDwM_neUVe7n48b34Wj7_uHzbfHouuBohFXxsleit6sBUDbpqm5bLmKIxRpm7ttoLGqm1vJOcy92JblKppLZOMY20NvyJfT_8e_Pw7YYh6dKHDYTATziloCQ1bimbwyz_gfk5-yrdpJqCRFRdMZKo9UV1uETz2-uBzff9HM9CLd73X79714l0D19l7Xr05B6TtiPZ98Sw6A99PAGYfR4dehy477NA6j13Udnb_T_kL326aRw</recordid><startdate>20070701</startdate><enddate>20070701</enddate><creator>Tavazzi, Eleonora</creator><creator>Dwyer, Michael G.</creator><creator>Weinstock-Guttman, Bianca</creator><creator>Lema, Jordan</creator><creator>Bastianello, Stefano</creator><creator>Bergamaschi, Roberto</creator><creator>Cosi, Vittorio</creator><creator>Benedict, Ralph H.B.</creator><creator>Munschauer, Frederick E.</creator><creator>Zivadinov, Robert</creator><general>Elsevier Inc</general><general>Elsevier Limited</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>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20070701</creationdate><title>Quantitative diffusion weighted imaging measures in patients with multiple sclerosis</title><author>Tavazzi, Eleonora ; Dwyer, Michael G. ; Weinstock-Guttman, Bianca ; Lema, Jordan ; Bastianello, Stefano ; Bergamaschi, Roberto ; Cosi, Vittorio ; Benedict, Ralph H.B. ; Munschauer, Frederick E. ; Zivadinov, Robert</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-f4a95fd5f0d2103a6683743e5aa9a48db206d9bfa73371091be7968d1713e4da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Automation</topic><topic>Brain - 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Academic</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tavazzi, Eleonora</au><au>Dwyer, Michael G.</au><au>Weinstock-Guttman, Bianca</au><au>Lema, Jordan</au><au>Bastianello, Stefano</au><au>Bergamaschi, Roberto</au><au>Cosi, Vittorio</au><au>Benedict, Ralph H.B.</au><au>Munschauer, Frederick E.</au><au>Zivadinov, Robert</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative diffusion weighted imaging measures in patients with multiple sclerosis</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2007-07-01</date><risdate>2007</risdate><volume>36</volume><issue>3</issue><spage>746</spage><epage>754</epage><pages>746-754</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract><![CDATA[Diffusion-weighted imaging (DWI) has been proposed as a sensitive measure of disease severity capable of detecting subtle changes in gray matter and white matter brain compartments in patients with multiple sclerosis (MS). However, DWI has been applied to the study of MS clinical subtypes in only a few studies. The objective of this study was to demonstrate the validity of a novel, fully automated method for the calculation of quantitative DWI measures. We also wanted to assess the correlation between whole brain (WB)-DWI variables and clinical and MRI measures of disease severity in a large cohort of MS patients. For this purpose we studied 432 consecutive MS patients (mean age 44.4±10.2 years), 16 patients with clinically isolated syndrome (CIS) and 38 normal controls (NC) using 1.5 T brain MRI. Clinical disease subtypes were as follows: 294 relapsing–remitting (RR), 123 secondary-progressive (SP) and 15 primary-progressive (PP). Mean disease duration was 12±10 years. Mean Expanded Disability Status Scale (EDSS) was 3.3±2.1. Brain parenchymal fraction (BPF), gray matter fraction (GMF) and white matter fraction (WMF) were calculated using a fully automated method. Mean parenchymal diffusivity (MPD) maps were created. DWI indices of peak position (PP), peak height (PH), MPD and entropy (ENT) were obtained. T2- and T1-lesion volumes (LV), EDSS, ambulation index (AI) and nine-hole peg test (9-HPT) were also assessed. MS patients had significantly lower BPF (d=1.26; p<0.001) and GMF (d=0.61; p=0.003), and higher ENT (d=1.2; p<0.0001), MPD (d=1.04; p<0.0001) and PH (d=0.47; p=0.045) than NC subjects. A GLM analysis, adjusted for age and multiple comparisons, revealed significant differences between different clinical subtypes for BPF, GMF, ENT, PH, PP, T2-LV and T1-LV (p<0.0001), WMF (p=0.001) and MPD (p=0.023). In RR and SP MS patients, ENT showed a more robust correlation with other MRI (r=0.54 to 0.67, p<0.0001) and clinical (r=0.31 to 0.36, p<0.0001) variables than MPD (r=0.23 to 0.41, p<0.001 for MRI and r=0.13 to 0.18; p=0.006 to p<0.001 for clinical variables). The GMF and BPF showed a slightly stronger relationship with all clinical variables (r=0.33 to 0.48; p<0.0001), when compared to both lesion and DWI measures. ENT (R2=0.28; p<0.0001) and GMF (R2=0.26; p<0.001) were best related with SP disease course. This study highlights the validity of DWI in discerning differences between NC and MS patients, as well as between different MS subtypes. ENT is a sensitive marker of overall brain damage that is strongly related to clinical impairment in patients with SP MS.]]></abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>17498974</pmid><doi>10.1016/j.neuroimage.2007.03.056</doi><tpages>9</tpages></addata></record> |
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| subjects | Adolescent Adult Aged Automation Brain - pathology Brain atrophy Clinical disability Cohort Studies Diffusion Diffusion imaging Diffusion Magnetic Resonance Imaging Entropy Female Humans Image Processing, Computer-Assisted Lesion volume Male Mean diffusivity Middle Aged MRI Multiple sclerosis Multiple Sclerosis - classification Multiple Sclerosis - pathology Neurologic Examination Neuropsychological Tests Pathology Prospective Studies Studies |
| title | Quantitative diffusion weighted imaging measures in patients with multiple sclerosis |
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