Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2
Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appea...
Ausführliche Beschreibung
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| Autor*in: |
Reitz, Sarah C. [verfasserIn] Hof, Stephanie-Michelle [verfasserIn] Fleischer, Vinzenz [verfasserIn] Brodski, Alla [verfasserIn] Gröger, Adriane [verfasserIn] Gracien, René-Maxime [verfasserIn] Droby, Amgad [verfasserIn] Steinmetz, Helmuth [verfasserIn] Ziemann, Ulf [verfasserIn] Zipp, Frauke [verfasserIn] Deichmann, Ralf [verfasserIn] Klein, Johannes C. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Brain imaging and behavior - New York, NY [u.a.] : Springer, 2007, 11(2016), 3 vom: 02. Mai, Seite 744-753 |
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| Übergeordnetes Werk: |
volume:11 ; year:2016 ; number:3 ; day:02 ; month:05 ; pages:744-753 |
| Links: |
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| DOI / URN: |
10.1007/s11682-016-9550-5 |
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SPR02171648X |
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| 520 | |a Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. | ||
| 650 | 4 | |a Quantitative MRI (qMRI) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Normal appearing white matter (NAWM) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Multiple sclerosis (MS) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Relapsing remitting multiple sclerosis (RRMS) |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Hof, Stephanie-Michelle |e verfasserin |4 aut | |
| 700 | 1 | |a Fleischer, Vinzenz |e verfasserin |4 aut | |
| 700 | 1 | |a Brodski, Alla |e verfasserin |4 aut | |
| 700 | 1 | |a Gröger, Adriane |e verfasserin |4 aut | |
| 700 | 1 | |a Gracien, René-Maxime |e verfasserin |4 aut | |
| 700 | 1 | |a Droby, Amgad |e verfasserin |4 aut | |
| 700 | 1 | |a Steinmetz, Helmuth |e verfasserin |4 aut | |
| 700 | 1 | |a Ziemann, Ulf |e verfasserin |4 aut | |
| 700 | 1 | |a Zipp, Frauke |e verfasserin |4 aut | |
| 700 | 1 | |a Deichmann, Ralf |e verfasserin |4 aut | |
| 700 | 1 | |a Klein, Johannes C. |e verfasserin |4 aut | |
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10.1007/s11682-016-9550-5 doi (DE-627)SPR02171648X (SPR)s11682-016-9550-5-e DE-627 ger DE-627 rakwb eng 150 ASE 44.90 bkl Reitz, Sarah C. verfasserin aut Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 Hof, Stephanie-Michelle verfasserin aut Fleischer, Vinzenz verfasserin aut Brodski, Alla verfasserin aut Gröger, Adriane verfasserin aut Gracien, René-Maxime verfasserin aut Droby, Amgad verfasserin aut Steinmetz, Helmuth verfasserin aut Ziemann, Ulf verfasserin aut Zipp, Frauke verfasserin aut Deichmann, Ralf verfasserin aut Klein, Johannes C. verfasserin aut Enthalten in Brain imaging and behavior New York, NY [u.a.] : Springer, 2007 11(2016), 3 vom: 02. Mai, Seite 744-753 (DE-627)537878033 (DE-600)2377165-3 1931-7565 nnns volume:11 year:2016 number:3 day:02 month:05 pages:744-753 https://dx.doi.org/10.1007/s11682-016-9550-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 11 2016 3 02 05 744-753 |
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10.1007/s11682-016-9550-5 doi (DE-627)SPR02171648X (SPR)s11682-016-9550-5-e DE-627 ger DE-627 rakwb eng 150 ASE 44.90 bkl Reitz, Sarah C. verfasserin aut Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 Hof, Stephanie-Michelle verfasserin aut Fleischer, Vinzenz verfasserin aut Brodski, Alla verfasserin aut Gröger, Adriane verfasserin aut Gracien, René-Maxime verfasserin aut Droby, Amgad verfasserin aut Steinmetz, Helmuth verfasserin aut Ziemann, Ulf verfasserin aut Zipp, Frauke verfasserin aut Deichmann, Ralf verfasserin aut Klein, Johannes C. verfasserin aut Enthalten in Brain imaging and behavior New York, NY [u.a.] : Springer, 2007 11(2016), 3 vom: 02. Mai, Seite 744-753 (DE-627)537878033 (DE-600)2377165-3 1931-7565 nnns volume:11 year:2016 number:3 day:02 month:05 pages:744-753 https://dx.doi.org/10.1007/s11682-016-9550-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 11 2016 3 02 05 744-753 |
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10.1007/s11682-016-9550-5 doi (DE-627)SPR02171648X (SPR)s11682-016-9550-5-e DE-627 ger DE-627 rakwb eng 150 ASE 44.90 bkl Reitz, Sarah C. verfasserin aut Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 Hof, Stephanie-Michelle verfasserin aut Fleischer, Vinzenz verfasserin aut Brodski, Alla verfasserin aut Gröger, Adriane verfasserin aut Gracien, René-Maxime verfasserin aut Droby, Amgad verfasserin aut Steinmetz, Helmuth verfasserin aut Ziemann, Ulf verfasserin aut Zipp, Frauke verfasserin aut Deichmann, Ralf verfasserin aut Klein, Johannes C. verfasserin aut Enthalten in Brain imaging and behavior New York, NY [u.a.] : Springer, 2007 11(2016), 3 vom: 02. Mai, Seite 744-753 (DE-627)537878033 (DE-600)2377165-3 1931-7565 nnns volume:11 year:2016 number:3 day:02 month:05 pages:744-753 https://dx.doi.org/10.1007/s11682-016-9550-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 11 2016 3 02 05 744-753 |
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10.1007/s11682-016-9550-5 doi (DE-627)SPR02171648X (SPR)s11682-016-9550-5-e DE-627 ger DE-627 rakwb eng 150 ASE 44.90 bkl Reitz, Sarah C. verfasserin aut Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 Hof, Stephanie-Michelle verfasserin aut Fleischer, Vinzenz verfasserin aut Brodski, Alla verfasserin aut Gröger, Adriane verfasserin aut Gracien, René-Maxime verfasserin aut Droby, Amgad verfasserin aut Steinmetz, Helmuth verfasserin aut Ziemann, Ulf verfasserin aut Zipp, Frauke verfasserin aut Deichmann, Ralf verfasserin aut Klein, Johannes C. verfasserin aut Enthalten in Brain imaging and behavior New York, NY [u.a.] : Springer, 2007 11(2016), 3 vom: 02. Mai, Seite 744-753 (DE-627)537878033 (DE-600)2377165-3 1931-7565 nnns volume:11 year:2016 number:3 day:02 month:05 pages:744-753 https://dx.doi.org/10.1007/s11682-016-9550-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 11 2016 3 02 05 744-753 |
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10.1007/s11682-016-9550-5 doi (DE-627)SPR02171648X (SPR)s11682-016-9550-5-e DE-627 ger DE-627 rakwb eng 150 ASE 44.90 bkl Reitz, Sarah C. verfasserin aut Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 Hof, Stephanie-Michelle verfasserin aut Fleischer, Vinzenz verfasserin aut Brodski, Alla verfasserin aut Gröger, Adriane verfasserin aut Gracien, René-Maxime verfasserin aut Droby, Amgad verfasserin aut Steinmetz, Helmuth verfasserin aut Ziemann, Ulf verfasserin aut Zipp, Frauke verfasserin aut Deichmann, Ralf verfasserin aut Klein, Johannes C. verfasserin aut Enthalten in Brain imaging and behavior New York, NY [u.a.] : Springer, 2007 11(2016), 3 vom: 02. Mai, Seite 744-753 (DE-627)537878033 (DE-600)2377165-3 1931-7565 nnns volume:11 year:2016 number:3 day:02 month:05 pages:744-753 https://dx.doi.org/10.1007/s11682-016-9550-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.90 ASE AR 11 2016 3 02 05 744-753 |
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Enthalten in Brain imaging and behavior 11(2016), 3 vom: 02. Mai, Seite 744-753 volume:11 year:2016 number:3 day:02 month:05 pages:744-753 |
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Enthalten in Brain imaging and behavior 11(2016), 3 vom: 02. Mai, Seite 744-753 volume:11 year:2016 number:3 day:02 month:05 pages:744-753 |
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Quantitative MRI (qMRI) Normal appearing white matter (NAWM) Multiple sclerosis (MS) Relapsing remitting multiple sclerosis (RRMS) |
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Reitz, Sarah C. @@aut@@ Hof, Stephanie-Michelle @@aut@@ Fleischer, Vinzenz @@aut@@ Brodski, Alla @@aut@@ Gröger, Adriane @@aut@@ Gracien, René-Maxime @@aut@@ Droby, Amgad @@aut@@ Steinmetz, Helmuth @@aut@@ Ziemann, Ulf @@aut@@ Zipp, Frauke @@aut@@ Deichmann, Ralf @@aut@@ Klein, Johannes C. @@aut@@ |
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Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. 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Reitz, Sarah C. |
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Reitz, Sarah C. ddc 150 bkl 44.90 misc Quantitative MRI (qMRI) misc Normal appearing white matter (NAWM) misc Multiple sclerosis (MS) misc Relapsing remitting multiple sclerosis (RRMS) Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 |
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150 ASE 44.90 bkl Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 Quantitative MRI (qMRI) (dpeaa)DE-He213 Normal appearing white matter (NAWM) (dpeaa)DE-He213 Multiple sclerosis (MS) (dpeaa)DE-He213 Relapsing remitting multiple sclerosis (RRMS) (dpeaa)DE-He213 |
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ddc 150 bkl 44.90 misc Quantitative MRI (qMRI) misc Normal appearing white matter (NAWM) misc Multiple sclerosis (MS) misc Relapsing remitting multiple sclerosis (RRMS) |
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ddc 150 bkl 44.90 misc Quantitative MRI (qMRI) misc Normal appearing white matter (NAWM) misc Multiple sclerosis (MS) misc Relapsing remitting multiple sclerosis (RRMS) |
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ddc 150 bkl 44.90 misc Quantitative MRI (qMRI) misc Normal appearing white matter (NAWM) misc Multiple sclerosis (MS) misc Relapsing remitting multiple sclerosis (RRMS) |
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Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 |
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Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 |
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Reitz, Sarah C. |
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Brain imaging and behavior |
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Brain imaging and behavior |
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Reitz, Sarah C. Hof, Stephanie-Michelle Fleischer, Vinzenz Brodski, Alla Gröger, Adriane Gracien, René-Maxime Droby, Amgad Steinmetz, Helmuth Ziemann, Ulf Zipp, Frauke Deichmann, Ralf Klein, Johannes C. |
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Reitz, Sarah C. |
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10.1007/s11682-016-9550-5 |
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multi-parametric quantitative mri of normal appearing white matter in multiple sclerosis, and the effect of disease activity on t2 |
| title_auth |
Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 |
| abstract |
Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. |
| abstractGer |
Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. |
| abstract_unstemmed |
Abstract White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions. |
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Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2 |
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Hof, Stephanie-Michelle Fleischer, Vinzenz Brodski, Alla Gröger, Adriane Gracien, René-Maxime Droby, Amgad Steinmetz, Helmuth Ziemann, Ulf Zipp, Frauke Deichmann, Ralf Klein, Johannes C. |
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Hof, Stephanie-Michelle Fleischer, Vinzenz Brodski, Alla Gröger, Adriane Gracien, René-Maxime Droby, Amgad Steinmetz, Helmuth Ziemann, Ulf Zipp, Frauke Deichmann, Ralf Klein, Johannes C. |
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| score |
7.400529 |