Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis

Background: Previous histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelin...

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Main Authors: Josefina Maranzano, Mahsa Dadar, Maryna Zhernovaia, Douglas L. Arnold, D. Louis Collins, Sridar Narayanan
Format: Article
Language:English
Published: Elsevier 2020-06-01
Series:NeuroImage
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920301774
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language English
format Article
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author Josefina Maranzano
Mahsa Dadar
Maryna Zhernovaia
Douglas L. Arnold
D. Louis Collins
Sridar Narayanan
spellingShingle Josefina Maranzano
Mahsa Dadar
Maryna Zhernovaia
Douglas L. Arnold
D. Louis Collins
Sridar Narayanan
Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
NeuroImage
Multiple sclerosis
Focal lesion
Diffusely abnormal white matter
Demyelination
Magnetization transfer ratio
Image normalization
author_facet Josefina Maranzano
Mahsa Dadar
Maryna Zhernovaia
Douglas L. Arnold
D. Louis Collins
Sridar Narayanan
author_sort Josefina Maranzano
title Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
title_short Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
title_full Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
title_fullStr Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
title_full_unstemmed Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis
title_sort automated separation of diffusely abnormal white matter from focal white matter lesions on mri in multiple sclerosis
publisher Elsevier
series NeuroImage
issn 1095-9572
publishDate 2020-06-01
description Background: Previous histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelination, axonal loss and immune cell density on histopathology, potentially offering distinct correlations with symptoms. Objectives: 1) To automate the separation of FWML and DAWM using T2w MRI intensity thresholds and to investigate their differences in magnetization transfer ratios (MTR), which are sensitive to myelin content; 2) to correlate MTR values in FWML and DAWM with normalized signal intensity values on fluid attenuated inversion recovery (FLAIR), T2w, and T1-weighted (T1w) contrasts, as well as with the ratio of T2w/T1w normalized values, in order to determine whether these normalized intensities can be used when MTR is not available. Methods: We used three MRI datasets: datasets 1 and 2 had 20 MS participants each, scanned with similar 3T MRI protocols in 2 centers, including: 3D T1w (MP2RAGE), 3D FLAIR, 2D T2w, and 3D magnetization-transfer (MT) contrasts. Dataset 3 consisted of 67 scans of participants enrolled in a multisite study and had T1w and T2w contrasts. We used the first dataset to develop an automated technique to separate FWML from DAWM and the second and third to validate the automation of the technique. We applied the automatic thresholds to all datasets to assess the overlap of the manual and the automated masks using Dice kappa. We also assessed differences in mean MTR values between NAWM, DAWM and FWML, using manually and automatically derived masks in datasets 1 and 2. Finally, we used the mean intensity of manually-traced areas of NAWM on T2w images as the normalization factor for each MRI contrast, and compared these with the normalized-intensity values obtained using automated NAWM (A-NAWM) masks as the normalization factor. ANOVA assessed the MTR differences across tissue types. Paired t-test or Wilcoxon signed-ranked test assessed FWML and DAWM differences between manual and automatically derived volumes. Pearson correlations assessed the relationship between MTR and normalized intensity values in the manual and automatically derived masks. Results: The mean Dice-kappa values for dataset 1 were: 0.79 for DAWM masks and 0.90 for FWML masks. In dataset 2, mean Dice-kappa values were: 0.78 for DAWM and 0.87 for FWML. In dataset 3, mean Dice-kappa values were 0.72 for DAWM, and 0.87 for FWML. Manual and automated DAWM and FWML volumes were not significantly different in all datasets. MTR values were significantly lower in manually and automatically derived FWML compared with DAWM in both datasets (dataset 1 manual: F ​= ​111,08, p ​< ​0.0001; automated: F ​= ​153.90, p ​< ​0.0001; dataset 2 manual: F ​= ​31.25, p ​< ​0.0001; automated: F ​= ​74.04, p ​< ​0.0001). In both datasets, manually derived FWML and DAWM MTR values showed significant correlations with normalized T1w (r ​= ​0.77 to 0.94) intensities. Conclusions: The separation of FWML and DAWM on MRI scans of MS patients using automated intensity thresholds on T2w images is feasible. MTR values are significantly lower in FWML than DAWM, and DAWM values are significantly lower than NAWM, reflecting potentially greater demyelination within focal lesions. T1w normalized intensity values exhibit a significant correlation with MTR values in both tissues of interest and could be used as a proxy to assess demyelination when MTR or other myelin-sensitive images are not available.
topic Multiple sclerosis
Focal lesion
Diffusely abnormal white matter
Demyelination
Magnetization transfer ratio
Image normalization
url http://www.sciencedirect.com/science/article/pii/S1053811920301774
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spelling doaj-28e38576659a49fdb3d0a70520c1647f2021-02-15T04:12:27ZengElsevierNeuroImage1095-95722020-06-01213116690Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosisJosefina Maranzano0Mahsa Dadar1Maryna Zhernovaia2Douglas L. Arnold3D. Louis Collins4Sridar Narayanan5Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, Quebec, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Corresponding author. University of Quebec in Trois-Rivieres, Department of Anatomy, Pavillon Leon-Provancher, Local 3501, 3351, boulevard des Forges, Trois-Rivieres, Quebec, G8Z 4M3, Canada.McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, CanadaDepartment of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, Quebec, CanadaMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, CanadaMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, CanadaMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, CanadaBackground: Previous histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelination, axonal loss and immune cell density on histopathology, potentially offering distinct correlations with symptoms. Objectives: 1) To automate the separation of FWML and DAWM using T2w MRI intensity thresholds and to investigate their differences in magnetization transfer ratios (MTR), which are sensitive to myelin content; 2) to correlate MTR values in FWML and DAWM with normalized signal intensity values on fluid attenuated inversion recovery (FLAIR), T2w, and T1-weighted (T1w) contrasts, as well as with the ratio of T2w/T1w normalized values, in order to determine whether these normalized intensities can be used when MTR is not available. Methods: We used three MRI datasets: datasets 1 and 2 had 20 MS participants each, scanned with similar 3T MRI protocols in 2 centers, including: 3D T1w (MP2RAGE), 3D FLAIR, 2D T2w, and 3D magnetization-transfer (MT) contrasts. Dataset 3 consisted of 67 scans of participants enrolled in a multisite study and had T1w and T2w contrasts. We used the first dataset to develop an automated technique to separate FWML from DAWM and the second and third to validate the automation of the technique. We applied the automatic thresholds to all datasets to assess the overlap of the manual and the automated masks using Dice kappa. We also assessed differences in mean MTR values between NAWM, DAWM and FWML, using manually and automatically derived masks in datasets 1 and 2. Finally, we used the mean intensity of manually-traced areas of NAWM on T2w images as the normalization factor for each MRI contrast, and compared these with the normalized-intensity values obtained using automated NAWM (A-NAWM) masks as the normalization factor. ANOVA assessed the MTR differences across tissue types. Paired t-test or Wilcoxon signed-ranked test assessed FWML and DAWM differences between manual and automatically derived volumes. Pearson correlations assessed the relationship between MTR and normalized intensity values in the manual and automatically derived masks. Results: The mean Dice-kappa values for dataset 1 were: 0.79 for DAWM masks and 0.90 for FWML masks. In dataset 2, mean Dice-kappa values were: 0.78 for DAWM and 0.87 for FWML. In dataset 3, mean Dice-kappa values were 0.72 for DAWM, and 0.87 for FWML. Manual and automated DAWM and FWML volumes were not significantly different in all datasets. MTR values were significantly lower in manually and automatically derived FWML compared with DAWM in both datasets (dataset 1 manual: F ​= ​111,08, p ​< ​0.0001; automated: F ​= ​153.90, p ​< ​0.0001; dataset 2 manual: F ​= ​31.25, p ​< ​0.0001; automated: F ​= ​74.04, p ​< ​0.0001). In both datasets, manually derived FWML and DAWM MTR values showed significant correlations with normalized T1w (r ​= ​0.77 to 0.94) intensities. Conclusions: The separation of FWML and DAWM on MRI scans of MS patients using automated intensity thresholds on T2w images is feasible. MTR values are significantly lower in FWML than DAWM, and DAWM values are significantly lower than NAWM, reflecting potentially greater demyelination within focal lesions. T1w normalized intensity values exhibit a significant correlation with MTR values in both tissues of interest and could be used as a proxy to assess demyelination when MTR or other myelin-sensitive images are not available.http://www.sciencedirect.com/science/article/pii/S1053811920301774Multiple sclerosisFocal lesionDiffusely abnormal white matterDemyelinationMagnetization transfer ratioImage normalization