Subcortical gray matter segmentation and voxel-based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis

Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it to voxel‐based analysis in multiple sclerosis (MS). Materials and Methods Voxel‐based variation in R2* and QSM within deep gray matter was exa...

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Published inJournal of magnetic resonance imaging Vol. 42; no. 6; pp. 1601 - 1610
Main Authors Cobzas, Dana, Sun, Hongfu, Walsh, Andrew J., Lebel, R. Marc, Blevins, Gregg, Wilman, Alan H.
Format Journal Article
LanguageEnglish
Published United States Blackwell Publishing Ltd 01.12.2015
Wiley Subscription Services, Inc
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Online AccessGet full text
ISSN1053-1807
1522-2586
1522-2586
DOI10.1002/jmri.24951

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Abstract Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it to voxel‐based analysis in multiple sclerosis (MS). Materials and Methods Voxel‐based variation in R2* and QSM within deep gray matter was examined and compared to standard whole‐structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1‐weighted images. Segmentation accuracy and scan–rescan reliability were tested. Results When considering only significant regions as returned by the multivariate voxel‐based analysis, increased R2* and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2*, regional analysis yielded at least 66‐fold improved P‐value significance in all nuclei over standard whole‐structure analysis, while for QSM only thalamus benefited, with 5‐fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high‐contrast QSM into the atlas. Voxel‐based reliability was highest for QSM (<1% variation). Conclusion Automatic segmentation of iron‐rich deep gray matter can be improved by incorporating QSM. Voxel‐based evaluation yielded increased R2* and QSM in MS subjects in all four nuclei studied with R2*, benefiting the most from localized analysis over whole‐structure measures. J. MAGN. RESON. IMAGING 2015;42:1601–1610.
AbstractList Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS). Materials and Methods Voxel-based variation in R2* and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1-weighted images. Segmentation accuracy and scan-rescan reliability were tested. Results When considering only significant regions as returned by the multivariate voxel-based analysis, increased R2* and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2*, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation). Conclusion Automatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2* and QSM in MS subjects in all four nuclei studied with R2*, benefiting the most from localized analysis over whole-structure measures. J. MAGN. RESON. IMAGING 2015;42:1601-1610.
Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R sub(2)*) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS). Materials and Methods Voxel-based variation in R sub(2)* and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T sub(1)-weighted images. Segmentation accuracy and scan-rescan reliability were tested. Results When considering only significant regions as returned by the multivariate voxel-based analysis, increased R sub(2)* and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R sub(2)*, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation). Conclusion Automatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R sub(2)* and QSM in MS subjects in all four nuclei studied with R sub(2)*, benefiting the most from localized analysis over whole-structure measures. J. MAGN. RESON. IMAGING 2015; 42:1601-1610.
Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it to voxel‐based analysis in multiple sclerosis (MS). Materials and Methods Voxel‐based variation in R2* and QSM within deep gray matter was examined and compared to standard whole‐structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1‐weighted images. Segmentation accuracy and scan–rescan reliability were tested. Results When considering only significant regions as returned by the multivariate voxel‐based analysis, increased R2* and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2*, regional analysis yielded at least 66‐fold improved P‐value significance in all nuclei over standard whole‐structure analysis, while for QSM only thalamus benefited, with 5‐fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high‐contrast QSM into the atlas. Voxel‐based reliability was highest for QSM (<1% variation). Conclusion Automatic segmentation of iron‐rich deep gray matter can be improved by incorporating QSM. Voxel‐based evaluation yielded increased R2* and QSM in MS subjects in all four nuclei studied with R2*, benefiting the most from localized analysis over whole‐structure measures. J. MAGN. RESON. IMAGING 2015;42:1601–1610.
To investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS).PURPOSETo investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS).Voxel-based variation in R2 * and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1 -weighted images. Segmentation accuracy and scan-rescan reliability were tested.MATERIALS AND METHODSVoxel-based variation in R2 * and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1 -weighted images. Segmentation accuracy and scan-rescan reliability were tested.When considering only significant regions as returned by the multivariate voxel-based analysis, increased R2 * and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2 *, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation).RESULTSWhen considering only significant regions as returned by the multivariate voxel-based analysis, increased R2 * and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2 *, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation).Automatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2 * and QSM in MS subjects in all four nuclei studied with R2 *, benefiting the most from localized analysis over whole-structure measures.CONCLUSIONAutomatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2 * and QSM in MS subjects in all four nuclei studied with R2 *, benefiting the most from localized analysis over whole-structure measures.
To investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to voxel-based analysis in multiple sclerosis (MS). Voxel-based variation in R2 * and QSM within deep gray matter was examined and compared to standard whole-structure analysis using 37 MS subjects and 37 matched controls. Deep gray matter nuclei (caudate, putamen, globus pallidus, and thalamus) were automatically segmented and morphed onto a custom atlas based on QSM and standard T1 -weighted images. Segmentation accuracy and scan-rescan reliability were tested. When considering only significant regions as returned by the multivariate voxel-based analysis, increased R2 * and QSM was found in MS subjects compared to controls in portions of all four nuclei studied (P < 0.002). For R2 *, regional analysis yielded at least 66-fold improved P-value significance in all nuclei over standard whole-structure analysis, while for QSM only thalamus benefited, with 5-fold improvement in significance. Improved segmentation over standard methods, particularly for globus pallidus (2.8 times higher Dice score), was achieved by incorporating high-contrast QSM into the atlas. Voxel-based reliability was highest for QSM (<1% variation). Automatic segmentation of iron-rich deep gray matter can be improved by incorporating QSM. Voxel-based evaluation yielded increased R2 * and QSM in MS subjects in all four nuclei studied with R2 *, benefiting the most from localized analysis over whole-structure measures.
Author Wilman, Alan H.
Sun, Hongfu
Cobzas, Dana
Lebel, R. Marc
Walsh, Andrew J.
Blevins, Gregg
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Keywords R2
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quantitative susceptibility mapping
multiple sclerosis
subcortical gray matter
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Snippet Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it...
To investigate subcortical gray matter segmentation using transverse relaxation rate (R2 *) and quantitative susceptibility mapping (QSM) and apply it to...
Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) and apply it...
Purpose To investigate subcortical gray matter segmentation using transverse relaxation rate (R sub(2)*) and quantitative susceptibility mapping (QSM) and...
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SubjectTerms Adult
Algorithms
Brain - pathology
brain iron
Female
Gray Matter - pathology
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Male
Middle Aged
Multiple sclerosis
Multiple Sclerosis - pathology
Pattern Recognition, Automated - methods
quantitative susceptibility mapping
Reproducibility of Results
segmentation
Sensitivity and Specificity
subcortical gray matter
Subtraction Technique
Young Adult
Title Subcortical gray matter segmentation and voxel-based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis
URI https://api.istex.fr/ark:/67375/WNG-4S2FN2MF-P/fulltext.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjmri.24951
https://www.ncbi.nlm.nih.gov/pubmed/25980643
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