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 in | Journal of magnetic resonance imaging Vol. 42; no. 6; pp. 1601 - 1610 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.12.2015
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1053-1807 1522-2586 1522-2586 |
DOI | 10.1002/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. |
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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 |
Author_xml | – sequence: 1 givenname: Dana surname: Cobzas fullname: Cobzas, Dana organization: Biomedical Engineering, University of Alberta, Edmonton, Canada – sequence: 2 givenname: Hongfu surname: Sun fullname: Sun, Hongfu organization: Biomedical Engineering, University of Alberta, Edmonton, Canada – sequence: 3 givenname: Andrew J. surname: Walsh fullname: Walsh, Andrew J. organization: Biomedical Engineering, University of Alberta, Edmonton, Canada – sequence: 4 givenname: R. Marc surname: Lebel fullname: Lebel, R. Marc organization: Biomedical Engineering, University of Alberta, Edmonton, Canada – sequence: 5 givenname: Gregg surname: Blevins fullname: Blevins, Gregg organization: Division of Neurology, University of Alberta, Edmonton, Canada – sequence: 6 givenname: Alan H. surname: Wilman fullname: Wilman, Alan H. email: wilman@ualberta.ca organization: Biomedical Engineering, University of Alberta, Edmonton, Canada |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25980643$$D View this record in MEDLINE/PubMed |
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Keywords | R2 segmentation brain iron quantitative susceptibility mapping multiple sclerosis subcortical gray matter |
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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 |
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