Spatial patterns of brain lesions assessed through covariance estimations of lesional voxels in multiple Sclerosis: The SPACE-MS technique
[Display omitted] •We present SPACE-MS, a tool to assess the spatial distribution of brain lesions.•SPACE-MS metrics mainly reflect caudality and spatial spreading of brain lesions.•More caudal and more widespread brain lesions correlate with worse disability.•SPACE-MS metrics can be automatically o...
Uloženo v:
| Vydáno v: | NeuroImage clinical Ročník 33; s. 102904 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Netherlands
Elsevier Inc
01.01.2022
Elsevier |
| Témata: | |
| ISSN: | 2213-1582, 2213-1582 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | [Display omitted]
•We present SPACE-MS, a tool to assess the spatial distribution of brain lesions.•SPACE-MS metrics mainly reflect caudality and spatial spreading of brain lesions.•More caudal and more widespread brain lesions correlate with worse disability.•SPACE-MS metrics can be automatically obtained using routine anatomical scans.•The usefulness of the SPACE-MS approach should be explored in other conditions.
Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient’s lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are.
We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders.
Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. |
|---|---|
| AbstractList | Graphical abstract Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient's lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions.Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient's lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. [Display omitted] •We present SPACE-MS, a tool to assess the spatial distribution of brain lesions.•SPACE-MS metrics mainly reflect caudality and spatial spreading of brain lesions.•More caudal and more widespread brain lesions correlate with worse disability.•SPACE-MS metrics can be automatically obtained using routine anatomical scans.•The usefulness of the SPACE-MS approach should be explored in other conditions. Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient’s lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. • We present SPACE-MS, a tool to assess the spatial distribution of brain lesions. • SPACE-MS metrics mainly reflect caudality and spatial spreading of brain lesions. • More caudal and more widespread brain lesions correlate with worse disability. • SPACE-MS metrics can be automatically obtained using routine anatomical scans. • The usefulness of the SPACE-MS approach should be explored in other conditions. Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient’s lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient's lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm ) and 2DT2-weighted (1x1x3mm ) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient’s lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are.We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders.Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions. |
| ArticleNumber | 102904 |
| Author | Calvi, Alberto Ciccarelli, Olga Cortese, Rosa Kanber, Baris Charalambous, Thalis Gandini Wheeler-Kingshott, Claudia A.M. Grussu, Francesco Chard, Declan T. Eshaghi, Arman Tur, Carmen De Angelis, Floriana Chataway, Jeremy Prados, Ferran Thompson, Alan J. |
| Author_xml | – sequence: 1 givenname: Carmen surname: Tur fullname: Tur, Carmen email: c.tur@ucl.ac.uk organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 2 givenname: Francesco surname: Grussu fullname: Grussu, Francesco organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 3 givenname: Floriana surname: De Angelis fullname: De Angelis, Floriana organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 4 givenname: Ferran surname: Prados fullname: Prados, Ferran organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 5 givenname: Baris surname: Kanber fullname: Kanber, Baris organization: Centre for Medical Image Computing, Medical Physics and Biomedical Engineering Department, University College London, UK – sequence: 6 givenname: Alberto surname: Calvi fullname: Calvi, Alberto organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 7 givenname: Arman surname: Eshaghi fullname: Eshaghi, Arman organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 8 givenname: Thalis surname: Charalambous fullname: Charalambous, Thalis organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 9 givenname: Rosa surname: Cortese fullname: Cortese, Rosa organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 10 givenname: Declan T. surname: Chard fullname: Chard, Declan T. organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 11 givenname: Jeremy surname: Chataway fullname: Chataway, Jeremy organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 12 givenname: Alan J. surname: Thompson fullname: Thompson, Alan J. organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 13 givenname: Olga surname: Ciccarelli fullname: Ciccarelli, Olga organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK – sequence: 14 givenname: Claudia A.M. surname: Gandini Wheeler-Kingshott fullname: Gandini Wheeler-Kingshott, Claudia A.M. email: c.wheeler-kingshott@ucl.ac.uk organization: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34875458$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFklFv0zAQxyM0xMbYF-AB5ZGXFttJHHdCk6ZqwKQhkDok3qyLc1ld3LjYTsW-Ap-a6zKmbRIjiuTkcv_f5e7-L7O93veYZa85m3LG5bvVtLfGTQUTnAJixspn2YEQvJjwSom9e8_72VGMK0aXYqyW8kW2X5SqrspKHWS_FxtIFlxOR8LQx9x3eRPA9rnDaD0FIEaku83TMvjhapkbv4VgoTeYY0x2TQA_CkcJ0bb-F7qYE2U9uGQ3DvOFcRh8tPE4v1zS69fT-dnk8yJPaJa9_Tngq-x5By7i0e15mH37cHY5_zS5-PLxfH56MTFS1GmiKuCsBlUbIzly0XYFNFIJKZsO64bJtjWi5YXoZm3DW8RZx00H7awAZSqE4jA7H7mth5XeBGogXGsPVt8EfLjSEBINF3UFjakLziVwWQplZqplAIIDK5umniGxTkbWZmjW2BrsUwD3APrwS2-X-spvtZJVKQtBgLe3gOBpBjHptY0GnYMe_RC1kExRL9Qxpb65X-uuyN9lUoIYEwzNOQbs7lI40zvT6JXemUbvTKNH05BIPRIZm242Sv9r3dPS96OUVo1bi0FHY5Fs0dqAJtE47dPyk0dy4yxlgfuB1xhXfghkpai5jkIzvdgZeudnGgajnr8T4PjfgP9V_wPxzAi7 |
| CitedBy_id | crossref_primary_10_1177_13524585241229969 crossref_primary_10_1093_braincomms_fcaf280 crossref_primary_10_1093_cercor_bhad041 crossref_primary_10_1177_13524585221139575 |
| Cites_doi | 10.1002/ana.24497 10.1136/jnnp-2018-318440 10.1177/1352458511410341 10.1371/journal.pone.0167274 10.1002/jmri.22178 10.1158/0008-5472.CAN-17-0339 10.1002/hbm.24760 10.1002/mrm.20741 10.3310/eme07030 10.1212/WNL.33.11.1444 10.1016/j.msard.2017.01.007 10.1016/S0140-6736(13)62242-4 10.1016/S0006-3495(94)80775-1 10.1212/WNL.0b013e3181feb26f 10.1002/ana.25637 10.1016/j.neuroimage.2012.07.059 10.1177/1352458519864933 10.1136/jnnp-2015-311102 10.1016/S1474-4422(10)70104-6 10.1001/jamaneurol.2019.2399 10.1093/brain/aww258 10.1016/S1474-4422(19)30485-5 10.1016/j.nicl.2018.07.012 10.1212/WNL.0b013e3181e042c4 10.1016/j.neuroimage.2017.04.034 10.1002/acn3.445 10.1177/2055217320906844 10.1111/bpa.12642 10.1148/radiol.2021200928 10.1016/j.neuroimage.2016.06.053 10.1016/S1474-4422(13)70144-3 10.1177/0961203318763533 10.1212/WNL.38.2.180 10.1109/TMI.2015.2418298 10.1038/s41746-019-0127-8 10.1111/ene.15023 10.1007/s00330-020-06803-y 10.1177/1352458519845105 10.1016/S0140-6736(18)30481-1 10.1002/ana.25145 10.1136/jnnp-2020-325421 10.1038/s41598-019-40437-5 |
| ContentType | Journal Article |
| Copyright | 2021 The Authors The Authors Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved. 2021 The Authors 2021 |
| Copyright_xml | – notice: 2021 The Authors – notice: The Authors – notice: Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved. – notice: 2021 The Authors 2021 |
| DBID | 6I. AAFTH AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM DOA |
| DOI | 10.1016/j.nicl.2021.102904 |
| DatabaseName | ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals (ODIN) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 2213-1582 |
| EndPage | 102904 |
| ExternalDocumentID | oai_doaj_org_article_5abc73116a16428c98d0aa21a04bb79e PMC8654632 34875458 10_1016_j_nicl_2021_102904 S221315822100348X 1_s2_0_S221315822100348X |
| Genre | Research Support, Non-U.S. Gov't Journal Article Observational Study |
| GrantInformation_xml | – fundername: Medical Research Council grantid: MR/T046422/1 – fundername: Medical Research Council grantid: MC_PC_13089 |
| GroupedDBID | .1- .FO 0R~ 1P~ 457 53G 5VS AAEDT AAEDW AAIKJ AALRI AAXUO AAYWO ABMAC ACGFS ACVFH ADBBV ADCNI ADEZE ADRAZ ADVLN AEUPX AEXQZ AFJKZ AFPUW AFRHN AFTJW AGHFR AIGII AITUG AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ AOIJS APXCP BAWUL BCNDV DIK EBS EJD FDB GROUPED_DOAJ HYE HZ~ IPNFZ IXB KQ8 M41 M48 M~E O-L O9- OK1 RIG ROL RPM SSZ Z5R 0SF 6I. AACTN AAFTH AFCTW NCXOZ AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM |
| ID | FETCH-LOGICAL-c627t-85a107a87cc61e12df3ab68266bfe7b06ddc2d132f9db1dee9f1cfad93a8c5ea3 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 6 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000731343200004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2213-1582 |
| IngestDate | Fri Oct 03 12:51:08 EDT 2025 Tue Sep 30 16:34:09 EDT 2025 Thu Sep 04 17:03:06 EDT 2025 Mon Jul 21 05:45:32 EDT 2025 Tue Nov 18 20:36:46 EST 2025 Wed Nov 05 20:43:28 EST 2025 Tue Jul 25 21:00:00 EDT 2023 Tue Feb 25 20:05:20 EST 2025 Tue Aug 26 16:33:11 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Lesion spatial distribution Multiple sclerosis SPACE-MS Magnetic resonance imaging Caudality Anisotropy |
| Language | English |
| License | This is an open access article under the CC BY license. Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c627t-85a107a87cc61e12df3ab68266bfe7b06ddc2d132f9db1dee9f1cfad93a8c5ea3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://doaj.org/article/5abc73116a16428c98d0aa21a04bb79e |
| PMID | 34875458 |
| PQID | 2608132107 |
| PQPubID | 23479 |
| PageCount | 1 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_5abc73116a16428c98d0aa21a04bb79e pubmedcentral_primary_oai_pubmedcentral_nih_gov_8654632 proquest_miscellaneous_2608132107 pubmed_primary_34875458 crossref_primary_10_1016_j_nicl_2021_102904 crossref_citationtrail_10_1016_j_nicl_2021_102904 elsevier_sciencedirect_doi_10_1016_j_nicl_2021_102904 elsevier_clinicalkeyesjournals_1_s2_0_S221315822100348X elsevier_clinicalkey_doi_10_1016_j_nicl_2021_102904 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-01-01 |
| PublicationDateYYYYMMDD | 2022-01-01 |
| PublicationDate_xml | – month: 01 year: 2022 text: 2022-01-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Netherlands |
| PublicationPlace_xml | – name: Netherlands |
| PublicationTitle | NeuroImage clinical |
| PublicationTitleAlternate | Neuroimage Clin |
| PublicationYear | 2022 |
| Publisher | Elsevier Inc Elsevier |
| Publisher_xml | – name: Elsevier Inc – name: Elsevier |
| References | Prados, Cardoso, Kanber (b0160) 2016; 139 Haider, Chung, Birch (b0170) 2021; 92 Meijer, Steenwijk, Douw, Schoonheim, Geurts (b0215) 2020; 143 Kanber, B., Nachev, P., Barkhof, F., et al. 2019. High-dimensional detection of imaging response to treatment in multiple sclerosis. NPJ Digit. Med. [online serial] 2:49. Accessed at: http://www.nature.com/articles/s41746-019-0127-8. Absinta, Sati, Masuzzo (b0040) 2019; 76 Chataway, Schuerer, Alsanousi (b0125) 2014; 383 Donohue, Jacqmin-Gadda, Le Goff (b0255) 2014; 10 Solana, Martinez-Heras, Martinez-Lapiscina (b0230) 2018; 20 Tur, Penny, Khaleeli (b0175) 2011; 17 He, Dagher, Chen (b0065) 2009; 132 Kurtzke (b0135) 1983; 33 Haider, Zrzavy, Hametner (b0205) 2016; 139 Thompson, Baranzini, Geurts, Hemmer, Ciccarelli (b0015) 2018; 391 Ziegler, Grabher, Thompson (b0220) 2018; 90 Eden, Gros, Badji (b0070) 2019; 142 Sethi, Yousry, Muhlert (b0150) 2016; 87 Tur, Grussu, Prados (b0235) 2020; 26 Brownlee, Altmann, Prados (b0095) 2019; 142 Mitchell, Archer, Chu (b0195) 2019; 40 Pantoni (b0010) 2010; 9 Cardoso, Modat, Wolz (b0165) 2015; 34 Naismith, Xu, Tutlam (b0035) 2010; 74 Frischer, Weigand, Guo (b0080) 2015; 78 Smith A. Symbol Digit Modalities Test: Manual. Los Angeles Western Psychological Services; 2007. . Ennis, Kindlmann (b0045) 2006; 55 Chung, Altmann, Barkhof (b0090) 2020; 87 Valverde, Cabezas, Roura (b0245) 2017; 155 Groeschel, S., Hagberg, G.E., Schultz, T., et al. 2016. Assessing white matter microstructure in brain regions with different myelin architecture using MRI. Lenglet C, editor. PLoS One [online serial]. 11:e0167274. Accessed at: https://dx.plos.org/10.1371/journal.pone.0167274. Grussu, Schneider, Tur (b0030) 2017; 4 Magliozzi, Reynolds, Calabrese (b0240) 2018; 28 van Griethuysen, Fedorov, Parmar (b0270) 2017; 77 Gaetano, L., Magnusson, B., Kindalova, P., et al. 2020. White matter lesion location correlates with disability in relapsing multiple sclerosis. Mult. Scler. J. – Exp. Transl. Clin. [online serial]. 6:205521732090684. Accessed at: http://journals.sagepub.com/doi/10.1177/2055217320906844. Chataway, De Angelis, Connick (b0120) 2020; 19 Eshaghi, Prados, Brownlee (b0055) 2018; 83 Basser, Mattiello, LeBihan (b0115) 1994; 66 Charalambous, T., Tur, C., Prados, F., et al. 2019. Structural network disruption markers explain disability in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry [online serial]. 90, 219–226. Accessed at: https://jnnp.bmj.com/lookup/doi/10.1136/jnnp-2018-318440. Kerbrat, Gros, Badji (b0100) 2020; 143 Jedynak, Lang, Liu (b0250) 2012; 63 Fisniku, Brex, Altmann (b0025) 2008; 131 Limkin, Reuzé, Carré (b0265) 2019; 9 Prados, F., Boada, I., Prats-Galino, A., et al. 2010. Analysis of new diffusion tensor imaging anisotropy measures in the three-phase plot. J. Magn. Reson. Imaging [online serial] 31, 1435–1444. Accessed at: https://onlinelibrary.wiley.com/doi/10.1002/jmri.22178. De Angelis, Connick, Parker (b0130) 2020; 7 Giovannoni, Cutter, Sormani (b0210) 2017; 12 Filippi, van den Heuvel, Fornito (b0060) 2013; 12 Correale, J., Gaitán, M.I., Ysrraelit, M.C., Fiol, M.P. 2016. Progressive multiple sclerosis: from pathogenic mechanisms to treatment. Brain [online serial]. aww258. Accessed at Connick, De Angelis, Parker (b0155) 2018; 8 Tintore, Rovira, Arrambide (b0085) 2010; 75 Cutter (b0140) 1999; 122 Tintore, Rovira, Río (b0020) 2015; 138 Conti, L., Preziosa, P., Meani, A., et al. 2021. Unraveling the substrates of cognitive impairment in multiple sclerosis: a multiparametric structural and functional MRI study. Eur. J. Neurol. [online serial] ene.15023. Accessed at: https://onlinelibrary.wiley.com/doi/10.1111/ene.15023. Cocozza, Cosottini, Signori (b0200) 2020; 30 Dekker, Sombekke, Balk (b0075) 2020; 26 Cannerfelt, Nystedt, Jönsen (b0005) 2018; 27 Paty, Oger, Kastrukoff (b0185) 1988; 38 Ligero, Garcia-Ruiz, Viaplana (b0275) 2021; 299 Cutter (10.1016/j.nicl.2021.102904_b0140) 1999; 122 Haider (10.1016/j.nicl.2021.102904_b0170) 2021; 92 Brownlee (10.1016/j.nicl.2021.102904_b0095) 2019; 142 Paty (10.1016/j.nicl.2021.102904_b0185) 1988; 38 Sethi (10.1016/j.nicl.2021.102904_b0150) 2016; 87 Prados (10.1016/j.nicl.2021.102904_b0160) 2016; 139 Cannerfelt (10.1016/j.nicl.2021.102904_b0005) 2018; 27 Basser (10.1016/j.nicl.2021.102904_b0115) 1994; 66 Pantoni (10.1016/j.nicl.2021.102904_b0010) 2010; 9 Thompson (10.1016/j.nicl.2021.102904_b0015) 2018; 391 Grussu (10.1016/j.nicl.2021.102904_b0030) 2017; 4 Haider (10.1016/j.nicl.2021.102904_b0205) 2016; 139 Absinta (10.1016/j.nicl.2021.102904_b0040) 2019; 76 Connick (10.1016/j.nicl.2021.102904_b0155) 2018; 8 Solana (10.1016/j.nicl.2021.102904_b0230) 2018; 20 Cocozza (10.1016/j.nicl.2021.102904_b0200) 2020; 30 10.1016/j.nicl.2021.102904_b0110 Limkin (10.1016/j.nicl.2021.102904_b0265) 2019; 9 Chung (10.1016/j.nicl.2021.102904_b0090) 2020; 87 Donohue (10.1016/j.nicl.2021.102904_b0255) 2014; 10 10.1016/j.nicl.2021.102904_b0190 Filippi (10.1016/j.nicl.2021.102904_b0060) 2013; 12 Eden (10.1016/j.nicl.2021.102904_b0070) 2019; 142 Kurtzke (10.1016/j.nicl.2021.102904_b0135) 1983; 33 Valverde (10.1016/j.nicl.2021.102904_b0245) 2017; 155 Chataway (10.1016/j.nicl.2021.102904_b0125) 2014; 383 10.1016/j.nicl.2021.102904_b0225 Fisniku (10.1016/j.nicl.2021.102904_b0025) 2008; 131 Chataway (10.1016/j.nicl.2021.102904_b0120) 2020; 19 10.1016/j.nicl.2021.102904_b0105 Magliozzi (10.1016/j.nicl.2021.102904_b0240) 2018; 28 He (10.1016/j.nicl.2021.102904_b0065) 2009; 132 Frischer (10.1016/j.nicl.2021.102904_b0080) 2015; 78 10.1016/j.nicl.2021.102904_b0260 10.1016/j.nicl.2021.102904_b0145 Tintore (10.1016/j.nicl.2021.102904_b0020) 2015; 138 Ziegler (10.1016/j.nicl.2021.102904_b0220) 2018; 90 Kerbrat (10.1016/j.nicl.2021.102904_b0100) 2020; 143 10.1016/j.nicl.2021.102904_b0180 Dekker (10.1016/j.nicl.2021.102904_b0075) 2020; 26 Eshaghi (10.1016/j.nicl.2021.102904_b0055) 2018; 83 Naismith (10.1016/j.nicl.2021.102904_b0035) 2010; 74 Tintore (10.1016/j.nicl.2021.102904_b0085) 2010; 75 Mitchell (10.1016/j.nicl.2021.102904_b0195) 2019; 40 Tur (10.1016/j.nicl.2021.102904_b0235) 2020; 26 Giovannoni (10.1016/j.nicl.2021.102904_b0210) 2017; 12 Tur (10.1016/j.nicl.2021.102904_b0175) 2011; 17 Jedynak (10.1016/j.nicl.2021.102904_b0250) 2012; 63 Meijer (10.1016/j.nicl.2021.102904_b0215) 2020; 143 Ennis (10.1016/j.nicl.2021.102904_b0045) 2006; 55 De Angelis (10.1016/j.nicl.2021.102904_b0130) 2020; 7 Cardoso (10.1016/j.nicl.2021.102904_b0165) 2015; 34 10.1016/j.nicl.2021.102904_b0050 Ligero (10.1016/j.nicl.2021.102904_b0275) 2021; 299 van Griethuysen (10.1016/j.nicl.2021.102904_b0270) 2017; 77 |
| References_xml | – volume: 142 start-page: 2276 year: 2019 end-page: 2287 ident: b0095 article-title: Early imaging predictors of long-term outcomes in relapse-onset multiple sclerosis publication-title: Brain [online serial] – volume: 78 start-page: 710 year: 2015 end-page: 721 ident: b0080 article-title: Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque publication-title: Ann. Neurol. [online serial] – volume: 26 start-page: 774 year: 2020 end-page: 785 ident: b0235 article-title: A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis publication-title: Mult. Scler. J. [online serial] – volume: 4 start-page: 663 year: 2017 end-page: 679 ident: b0030 article-title: Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? publication-title: Ann. Clin. Transl. Neurol. [online serial] – volume: 12 start-page: 70 year: 2017 end-page: 78 ident: b0210 article-title: Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses publication-title: Mult. Scler. Relat. Disord. [online serial] – volume: 12 start-page: 1189 year: 2013 end-page: 1199 ident: b0060 article-title: Assessment of system dysfunction in the brain through MRI-based connectomics publication-title: Lancet Neurol. [online serial] – reference: Gaetano, L., Magnusson, B., Kindalova, P., et al. 2020. White matter lesion location correlates with disability in relapsing multiple sclerosis. Mult. Scler. J. – Exp. Transl. Clin. [online serial]. 6:205521732090684. Accessed at: http://journals.sagepub.com/doi/10.1177/2055217320906844. – volume: 76 start-page: 1474 year: 2019 ident: b0040 article-title: Association of chronic active multiple sclerosis lesions with disability in vivo publication-title: JAMA Neurol. [online serial] – volume: 143 start-page: 2089 year: 2020 end-page: 2105 ident: b0100 article-title: Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability publication-title: Brain [online serial] – volume: 383 start-page: 2213 year: 2014 end-page: 2221 ident: b0125 article-title: Effect of high-dose simvastatin on brain atrophy and disability in secondary progressive multiple sclerosis (MS-STAT): a randomised, placebo-controlled, phase 2 trial publication-title: Lancet [online serial] – reference: Correale, J., Gaitán, M.I., Ysrraelit, M.C., Fiol, M.P. 2016. Progressive multiple sclerosis: from pathogenic mechanisms to treatment. Brain [online serial]. aww258. Accessed at: – reference: Charalambous, T., Tur, C., Prados, F., et al. 2019. Structural network disruption markers explain disability in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry [online serial]. 90, 219–226. Accessed at: https://jnnp.bmj.com/lookup/doi/10.1136/jnnp-2018-318440. – volume: 9 start-page: 689 year: 2010 end-page: 701 ident: b0010 article-title: Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges publication-title: Lancet Neurol. [online serial] – reference: Prados, F., Boada, I., Prats-Galino, A., et al. 2010. Analysis of new diffusion tensor imaging anisotropy measures in the three-phase plot. J. Magn. Reson. Imaging [online serial] 31, 1435–1444. Accessed at: https://onlinelibrary.wiley.com/doi/10.1002/jmri.22178. – volume: 92 start-page: 839 year: 2021 end-page: 846 ident: b0170 article-title: Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up publication-title: J. Neurol. Neurosurg. Psychiatry [online serial] – volume: 132 start-page: 3366 year: 2009 end-page: 3379 ident: b0065 article-title: Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load publication-title: Brain [online serial] – volume: 28 start-page: 735 year: 2018 end-page: 742 ident: b0240 article-title: MRI of cortical lesions and its use in studying their role in MS pathogenesis and disease course publication-title: Brain Pathol. [online serial] – volume: 26 start-page: 1381 year: 2020 end-page: 1391 ident: b0075 article-title: Infratentorial and spinal cord lesions: cumulative predictors of long-term disability? publication-title: Mult. Scler. J. [online serial] – reference: Kanber, B., Nachev, P., Barkhof, F., et al. 2019. High-dimensional detection of imaging response to treatment in multiple sclerosis. NPJ Digit. Med. [online serial] 2:49. Accessed at: http://www.nature.com/articles/s41746-019-0127-8. – volume: 391 start-page: 1622 year: 2018 end-page: 1636 ident: b0015 article-title: Multiple sclerosis publication-title: Lancet [online serial] – volume: 87 start-page: 750 year: 2016 end-page: 753 ident: b0150 article-title: A longitudinal study of cortical grey matter lesion subtypes in relapse-onset multiple sclerosis publication-title: J. Neurol. Neurosurg. Psychiatry [online serial] – volume: 139 start-page: 807 year: 2016 end-page: 815 ident: b0205 article-title: The topograpy of demyelination and neurodegeneration in the multiple sclerosis brain publication-title: Brain [online serial] – reference: Groeschel, S., Hagberg, G.E., Schultz, T., et al. 2016. Assessing white matter microstructure in brain regions with different myelin architecture using MRI. Lenglet C, editor. PLoS One [online serial]. 11:e0167274. Accessed at: https://dx.plos.org/10.1371/journal.pone.0167274. – reference: Smith A. Symbol Digit Modalities Test: Manual. Los Angeles Western Psychological Services; 2007. – volume: 7 start-page: 1 year: 2020 end-page: 72 ident: b0130 article-title: Amiloride, fluoxetine or riluzole to reduce brain volume loss in secondary progressive multiple sclerosis: the MS-SMART four-arm RCT publication-title: Effic. Mech. Eval. [online serial] – volume: 87 start-page: 63 year: 2020 end-page: 74 ident: b0090 article-title: A 30-year clinical and magnetic resonance imaging observational study of multiple sclerosis and clinically isolated syndromes publication-title: Ann. Neurol. [online serial] – volume: 27 start-page: 1140 year: 2018 end-page: 1149 ident: b0005 article-title: White matter lesions and brain atrophy in systemic lupus erythematosus patients: correlation to cognitive dysfunction in a cohort of systemic lupus erythematosus patients using different definition models for neuropsychiatric systemic lupus erythematosus publication-title: Lupus [online serial]. – volume: 143 start-page: 150 year: 2020 end-page: 160 ident: b0215 article-title: Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis publication-title: Brain [online serial] – volume: 66 start-page: 259 year: 1994 end-page: 267 ident: b0115 article-title: MR diffusion tensor spectroscopy and imaging publication-title: Biophys. J. [online serial] – volume: 83 start-page: 210 year: 2018 end-page: 222 ident: b0055 article-title: Deep gray matter volume loss drives disability worsening in multiple sclerosis publication-title: Ann. Neurol. [online serial] – volume: 10 year: 2014 ident: b0255 article-title: Estimating long-term multivariate progression from short-term data publication-title: Alzheimer’s Dement [online serial] – volume: 75 start-page: 1933 year: 2010 end-page: 1938 ident: b0085 article-title: Brainstem lesions in clinically isolated syndromes publication-title: Neurology [online serial] – volume: 9 start-page: 4329 year: 2019 ident: b0265 article-title: The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features publication-title: Sci. Rep. [online serial] – volume: 40 start-page: 5094 year: 2019 end-page: 5107 ident: b0195 article-title: Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism publication-title: Hum. Brain. Mapp. [online serial]. – volume: 30 start-page: 4586 year: 2020 end-page: 4594 ident: b0200 article-title: A clinically feasible 7-Tesla protocol for the identification of cortical lesions in Multiple Sclerosis publication-title: Eur. Radiol. [online serial] – volume: 74 start-page: 1694 year: 2010 end-page: 1701 ident: b0035 article-title: Increased diffusivity in acute multiple sclerosis lesions predicts risk of black hole publication-title: Neurology [online serial] – volume: 139 start-page: 376 year: 2016 end-page: 384 ident: b0160 article-title: A multi-time-point modality-agnostic patch-based method for lesion filling in multiple sclerosis publication-title: Neuroimage [online serial] – volume: 77 start-page: e104 year: 2017 end-page: e107 ident: b0270 article-title: Computational radiomics system to decode the radiographic phenotype publication-title: Cancer Res. [online serial] – volume: 33 start-page: 1444 year: 1983 ident: b0135 article-title: Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS) publication-title: Neurology [online serial] – volume: 138 start-page: 1863 year: 2015 end-page: 1874 ident: b0020 article-title: Defining high, medium and low impact prognostic factors for developing multiple sclerosis publication-title: Brain [online serial] – volume: 131 start-page: 808 year: 2008 end-page: 817 ident: b0025 article-title: Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis publication-title: Brain [online serial] – volume: 90 start-page: e1257 year: 2018 end-page: e1266 ident: b0220 article-title: Progressive neurodegeneration following spinal cord injury publication-title: Neurology [online serial] – volume: 155 start-page: 159 year: 2017 end-page: 168 ident: b0245 article-title: Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach publication-title: Neuroimage [online serial] – volume: 142 start-page: 633 year: 2019 end-page: 646 ident: b0070 article-title: Spatial distribution of multiple sclerosis lesions in the cervical spinal cord publication-title: Brain [online serial] – volume: 122 start-page: 871 year: 1999 end-page: 882 ident: b0140 article-title: Development of a multiple sclerosis functional composite as a clinical trial outcome measure publication-title: Brain [online serial] – volume: 17 start-page: 1324 year: 2011 end-page: 1332 ident: b0175 article-title: Grey matter damage and overall cognitive impairment in primary progressive multiple sclerosis publication-title: Mult. Scler. J. [online serial]. – reference: . – volume: 20 start-page: 161 year: 2018 end-page: 168 ident: b0230 article-title: Magnetic resonance markers of tissue damage related to connectivity disruption in multiple sclerosis publication-title: NeuroImage Clin. [online serial] – volume: 8 year: 2018 ident: b0155 article-title: Multiple sclerosis-secondary progressive multi-arm randomisation trial (MS-SMART): a multiarm phase IIb randomised, double-blind, placebo-controlled clinical trial comparing the efficacy of three neuroprotective drugs in secondary progressive multiple scl publication-title: BMJ Open [online serial] – volume: 299 start-page: 109 year: 2021 end-page: 119 ident: b0275 article-title: A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors publication-title: Radiology [online serial] – volume: 19 start-page: 214 year: 2020 end-page: 225 ident: b0120 article-title: Efficacy of three neuroprotective drugs in secondary progressive multiple sclerosis (MS-SMART): a phase 2b, multiarm, double-blind, randomised placebo-controlled trial publication-title: Lancet Neurol. [online serial] – volume: 38 start-page: 180 year: 1988 ident: b0185 article-title: MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT publication-title: Neurology [online serial] – volume: 34 start-page: 1976 year: 2015 end-page: 1988 ident: b0165 article-title: Geodesic information flows: spatially-variant graphs and their application to segmentation and fusion publication-title: IEEE Trans. Med. Imaging [online serial] – volume: 63 start-page: 1478 year: 2012 end-page: 1486 ident: b0250 article-title: A computational neurodegenerative disease progression score: Method and results with the Alzheimer’s disease neuroimaging initiative cohort publication-title: Neuroimage [online serial] – volume: 55 start-page: 136 year: 2006 end-page: 146 ident: b0045 article-title: Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images publication-title: Magn. Reson. Med. [online serial] – reference: Conti, L., Preziosa, P., Meani, A., et al. 2021. Unraveling the substrates of cognitive impairment in multiple sclerosis: a multiparametric structural and functional MRI study. Eur. J. Neurol. [online serial] ene.15023. Accessed at: https://onlinelibrary.wiley.com/doi/10.1111/ene.15023. – volume: 78 start-page: 710 year: 2015 ident: 10.1016/j.nicl.2021.102904_b0080 article-title: Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque publication-title: Ann. Neurol. [online serial] doi: 10.1002/ana.24497 – volume: 142 start-page: 633 year: 2019 ident: 10.1016/j.nicl.2021.102904_b0070 article-title: Spatial distribution of multiple sclerosis lesions in the cervical spinal cord publication-title: Brain [online serial] – ident: 10.1016/j.nicl.2021.102904_b0105 doi: 10.1136/jnnp-2018-318440 – volume: 17 start-page: 1324 year: 2011 ident: 10.1016/j.nicl.2021.102904_b0175 article-title: Grey matter damage and overall cognitive impairment in primary progressive multiple sclerosis publication-title: Mult. Scler. J. [online serial]. doi: 10.1177/1352458511410341 – volume: 143 start-page: 150 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0215 article-title: Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis publication-title: Brain [online serial] – ident: 10.1016/j.nicl.2021.102904_b0190 doi: 10.1371/journal.pone.0167274 – ident: 10.1016/j.nicl.2021.102904_b0050 doi: 10.1002/jmri.22178 – volume: 122 start-page: 871 year: 1999 ident: 10.1016/j.nicl.2021.102904_b0140 article-title: Development of a multiple sclerosis functional composite as a clinical trial outcome measure publication-title: Brain [online serial] – volume: 77 start-page: e104 year: 2017 ident: 10.1016/j.nicl.2021.102904_b0270 article-title: Computational radiomics system to decode the radiographic phenotype publication-title: Cancer Res. [online serial] doi: 10.1158/0008-5472.CAN-17-0339 – volume: 40 start-page: 5094 year: 2019 ident: 10.1016/j.nicl.2021.102904_b0195 article-title: Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism publication-title: Hum. Brain. Mapp. [online serial]. doi: 10.1002/hbm.24760 – volume: 55 start-page: 136 year: 2006 ident: 10.1016/j.nicl.2021.102904_b0045 article-title: Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images publication-title: Magn. Reson. Med. [online serial] doi: 10.1002/mrm.20741 – volume: 7 start-page: 1 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0130 article-title: Amiloride, fluoxetine or riluzole to reduce brain volume loss in secondary progressive multiple sclerosis: the MS-SMART four-arm RCT publication-title: Effic. Mech. Eval. [online serial] doi: 10.3310/eme07030 – volume: 33 start-page: 1444 year: 1983 ident: 10.1016/j.nicl.2021.102904_b0135 article-title: Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS) publication-title: Neurology [online serial] doi: 10.1212/WNL.33.11.1444 – volume: 12 start-page: 70 year: 2017 ident: 10.1016/j.nicl.2021.102904_b0210 article-title: Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses publication-title: Mult. Scler. Relat. Disord. [online serial] doi: 10.1016/j.msard.2017.01.007 – volume: 383 start-page: 2213 year: 2014 ident: 10.1016/j.nicl.2021.102904_b0125 article-title: Effect of high-dose simvastatin on brain atrophy and disability in secondary progressive multiple sclerosis (MS-STAT): a randomised, placebo-controlled, phase 2 trial publication-title: Lancet [online serial] doi: 10.1016/S0140-6736(13)62242-4 – volume: 66 start-page: 259 year: 1994 ident: 10.1016/j.nicl.2021.102904_b0115 article-title: MR diffusion tensor spectroscopy and imaging publication-title: Biophys. J. [online serial] doi: 10.1016/S0006-3495(94)80775-1 – volume: 75 start-page: 1933 year: 2010 ident: 10.1016/j.nicl.2021.102904_b0085 article-title: Brainstem lesions in clinically isolated syndromes publication-title: Neurology [online serial] doi: 10.1212/WNL.0b013e3181feb26f – ident: 10.1016/j.nicl.2021.102904_b0145 – volume: 10 year: 2014 ident: 10.1016/j.nicl.2021.102904_b0255 article-title: Estimating long-term multivariate progression from short-term data publication-title: Alzheimer’s Dement [online serial] – volume: 87 start-page: 63 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0090 article-title: A 30-year clinical and magnetic resonance imaging observational study of multiple sclerosis and clinically isolated syndromes publication-title: Ann. Neurol. [online serial] doi: 10.1002/ana.25637 – volume: 63 start-page: 1478 year: 2012 ident: 10.1016/j.nicl.2021.102904_b0250 article-title: A computational neurodegenerative disease progression score: Method and results with the Alzheimer’s disease neuroimaging initiative cohort publication-title: Neuroimage [online serial] doi: 10.1016/j.neuroimage.2012.07.059 – volume: 26 start-page: 1381 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0075 article-title: Infratentorial and spinal cord lesions: cumulative predictors of long-term disability? publication-title: Mult. Scler. J. [online serial] doi: 10.1177/1352458519864933 – volume: 87 start-page: 750 year: 2016 ident: 10.1016/j.nicl.2021.102904_b0150 article-title: A longitudinal study of cortical grey matter lesion subtypes in relapse-onset multiple sclerosis publication-title: J. Neurol. Neurosurg. Psychiatry [online serial] doi: 10.1136/jnnp-2015-311102 – volume: 9 start-page: 689 year: 2010 ident: 10.1016/j.nicl.2021.102904_b0010 article-title: Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges publication-title: Lancet Neurol. [online serial] doi: 10.1016/S1474-4422(10)70104-6 – volume: 138 start-page: 1863 year: 2015 ident: 10.1016/j.nicl.2021.102904_b0020 article-title: Defining high, medium and low impact prognostic factors for developing multiple sclerosis publication-title: Brain [online serial] – volume: 76 start-page: 1474 year: 2019 ident: 10.1016/j.nicl.2021.102904_b0040 article-title: Association of chronic active multiple sclerosis lesions with disability in vivo publication-title: JAMA Neurol. [online serial] doi: 10.1001/jamaneurol.2019.2399 – ident: 10.1016/j.nicl.2021.102904_b0260 doi: 10.1093/brain/aww258 – volume: 90 start-page: e1257 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0220 article-title: Progressive neurodegeneration following spinal cord injury publication-title: Neurology [online serial] – volume: 19 start-page: 214 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0120 article-title: Efficacy of three neuroprotective drugs in secondary progressive multiple sclerosis (MS-SMART): a phase 2b, multiarm, double-blind, randomised placebo-controlled trial publication-title: Lancet Neurol. [online serial] doi: 10.1016/S1474-4422(19)30485-5 – volume: 20 start-page: 161 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0230 article-title: Magnetic resonance markers of tissue damage related to connectivity disruption in multiple sclerosis publication-title: NeuroImage Clin. [online serial] doi: 10.1016/j.nicl.2018.07.012 – volume: 74 start-page: 1694 year: 2010 ident: 10.1016/j.nicl.2021.102904_b0035 article-title: Increased diffusivity in acute multiple sclerosis lesions predicts risk of black hole publication-title: Neurology [online serial] doi: 10.1212/WNL.0b013e3181e042c4 – volume: 155 start-page: 159 year: 2017 ident: 10.1016/j.nicl.2021.102904_b0245 article-title: Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach publication-title: Neuroimage [online serial] doi: 10.1016/j.neuroimage.2017.04.034 – volume: 131 start-page: 808 year: 2008 ident: 10.1016/j.nicl.2021.102904_b0025 article-title: Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis publication-title: Brain [online serial] – volume: 139 start-page: 807 year: 2016 ident: 10.1016/j.nicl.2021.102904_b0205 article-title: The topograpy of demyelination and neurodegeneration in the multiple sclerosis brain publication-title: Brain [online serial] – volume: 4 start-page: 663 year: 2017 ident: 10.1016/j.nicl.2021.102904_b0030 article-title: Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? publication-title: Ann. Clin. Transl. Neurol. [online serial] doi: 10.1002/acn3.445 – volume: 142 start-page: 2276 year: 2019 ident: 10.1016/j.nicl.2021.102904_b0095 article-title: Early imaging predictors of long-term outcomes in relapse-onset multiple sclerosis publication-title: Brain [online serial] – ident: 10.1016/j.nicl.2021.102904_b0225 doi: 10.1177/2055217320906844 – volume: 28 start-page: 735 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0240 article-title: MRI of cortical lesions and its use in studying their role in MS pathogenesis and disease course publication-title: Brain Pathol. [online serial] doi: 10.1111/bpa.12642 – volume: 8 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0155 article-title: Multiple sclerosis-secondary progressive multi-arm randomisation trial (MS-SMART): a multiarm phase IIb randomised, double-blind, placebo-controlled clinical trial comparing the efficacy of three neuroprotective drugs in secondary progressive multiple scl publication-title: BMJ Open [online serial] – volume: 299 start-page: 109 year: 2021 ident: 10.1016/j.nicl.2021.102904_b0275 article-title: A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors publication-title: Radiology [online serial] doi: 10.1148/radiol.2021200928 – volume: 139 start-page: 376 year: 2016 ident: 10.1016/j.nicl.2021.102904_b0160 article-title: A multi-time-point modality-agnostic patch-based method for lesion filling in multiple sclerosis publication-title: Neuroimage [online serial] doi: 10.1016/j.neuroimage.2016.06.053 – volume: 143 start-page: 2089 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0100 article-title: Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability publication-title: Brain [online serial] – volume: 12 start-page: 1189 year: 2013 ident: 10.1016/j.nicl.2021.102904_b0060 article-title: Assessment of system dysfunction in the brain through MRI-based connectomics publication-title: Lancet Neurol. [online serial] doi: 10.1016/S1474-4422(13)70144-3 – volume: 27 start-page: 1140 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0005 article-title: White matter lesions and brain atrophy in systemic lupus erythematosus patients: correlation to cognitive dysfunction in a cohort of systemic lupus erythematosus patients using different definition models for neuropsychiatric systemic lupus erythematosus publication-title: Lupus [online serial]. doi: 10.1177/0961203318763533 – volume: 132 start-page: 3366 year: 2009 ident: 10.1016/j.nicl.2021.102904_b0065 article-title: Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load publication-title: Brain [online serial] – volume: 38 start-page: 180 year: 1988 ident: 10.1016/j.nicl.2021.102904_b0185 article-title: MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT publication-title: Neurology [online serial] doi: 10.1212/WNL.38.2.180 – volume: 34 start-page: 1976 year: 2015 ident: 10.1016/j.nicl.2021.102904_b0165 article-title: Geodesic information flows: spatially-variant graphs and their application to segmentation and fusion publication-title: IEEE Trans. Med. Imaging [online serial] doi: 10.1109/TMI.2015.2418298 – ident: 10.1016/j.nicl.2021.102904_b0110 doi: 10.1038/s41746-019-0127-8 – ident: 10.1016/j.nicl.2021.102904_b0180 doi: 10.1111/ene.15023 – volume: 30 start-page: 4586 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0200 article-title: A clinically feasible 7-Tesla protocol for the identification of cortical lesions in Multiple Sclerosis publication-title: Eur. Radiol. [online serial] doi: 10.1007/s00330-020-06803-y – volume: 26 start-page: 774 year: 2020 ident: 10.1016/j.nicl.2021.102904_b0235 article-title: A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis publication-title: Mult. Scler. J. [online serial] doi: 10.1177/1352458519845105 – volume: 391 start-page: 1622 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0015 article-title: Multiple sclerosis publication-title: Lancet [online serial] doi: 10.1016/S0140-6736(18)30481-1 – volume: 83 start-page: 210 year: 2018 ident: 10.1016/j.nicl.2021.102904_b0055 article-title: Deep gray matter volume loss drives disability worsening in multiple sclerosis publication-title: Ann. Neurol. [online serial] doi: 10.1002/ana.25145 – volume: 92 start-page: 839 year: 2021 ident: 10.1016/j.nicl.2021.102904_b0170 article-title: Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up publication-title: J. Neurol. Neurosurg. Psychiatry [online serial] doi: 10.1136/jnnp-2020-325421 – volume: 9 start-page: 4329 year: 2019 ident: 10.1016/j.nicl.2021.102904_b0265 article-title: The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features publication-title: Sci. Rep. [online serial] doi: 10.1038/s41598-019-40437-5 |
| SSID | ssj0000800766 |
| Score | 2.2882557 |
| Snippet | [Display omitted]
•We present SPACE-MS, a tool to assess the spatial distribution of brain lesions.•SPACE-MS metrics mainly reflect caudality and spatial... Graphical abstract Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white... • We present SPACE-MS, a tool to assess the spatial distribution of brain lesions. • SPACE-MS metrics mainly reflect caudality and spatial spreading of brain... |
| SourceID | doaj pubmedcentral proquest pubmed crossref elsevier |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 102904 |
| SubjectTerms | Anisotropy Brain - diagnostic imaging Brain - pathology Caudality Humans Lesion spatial distribution Magnetic resonance imaging Magnetic Resonance Imaging - methods Multiple sclerosis Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - pathology Multiple Sclerosis, Chronic Progressive - diagnostic imaging Multiple Sclerosis, Chronic Progressive - pathology Radiology Regular SPACE-MS White Matter - pathology |
| Title | Spatial patterns of brain lesions assessed through covariance estimations of lesional voxels in multiple Sclerosis: The SPACE-MS technique |
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S221315822100348X https://www.clinicalkey.es/playcontent/1-s2.0-S221315822100348X https://dx.doi.org/10.1016/j.nicl.2021.102904 https://www.ncbi.nlm.nih.gov/pubmed/34875458 https://www.proquest.com/docview/2608132107 https://pubmed.ncbi.nlm.nih.gov/PMC8654632 https://doaj.org/article/5abc73116a16428c98d0aa21a04bb79e |
| Volume | 33 |
| WOSCitedRecordID | wos000731343200004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2213-1582 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000800766 issn: 2213-1582 databaseCode: DOA dateStart: 20120101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2213-1582 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000800766 issn: 2213-1582 databaseCode: M~E dateStart: 20120101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LbxMxELagQogL4k14VEbihlasvQ_b3EqVikuqSgEpN8tPkaraVN004sQP4Fcz4_VGCaD2wiWHZMfe9Xyx51t7viHkvbCxlMbIorRMFrUCumOUq4pYGskAIMYHn4pNiNNTuVios51SX3gmbJAHHgbuY2OsExVjrWEYKjslfWkMZ6asrRUq4OxbCrVDps5zHCTSRiXnrCpYI3nOmBkOd6HqLJBDzlC6QOUqbeOqlMT79xanv4PPP89Q7ixKJ4_IwxxN0qPhKR6TO6F7Qu7P8n75U_ILKw4DwuhlktHserqK1GJVCHoR8D1ZT03a9Q2e5oo91K02wJ8RDBQVOIbUxmQ4mEBrm9UPuGsKrYznEekc-odHW_afKCCPzs-OjqfFbE63GrHPyLeT6dfjL0WuvlC4lot1IRsD1NBI4VzLAuM-Vsa2wEZaG4OwZeu94x7IbFTeMh-CisxF41VlpGuCqZ6Tg27VhZeECphXTAAvybato4oGebGyISYxfVdPCBtHX7ssTY4VMi70eAbtXKPHNHpMDx6bkA9bm8tBmOPGqz-jU7dXoqh2-gKgpjPU9G1Qm5BqhIQe81ZhpoWGljd2Lf5lFfo8WfSa6Z7rUs8RqohUYOFlVcvFhDRbyxwPDXHOrT2-G_GqYbLAHSDThdV1r4G8SoZZW2JCXgz43Q5JhdS1biTc7x6y98Zs_5du-T0JkkvMiKv4q_8xyK_JA44ZJukt1xtysL66Dm_JPbdZL_urQ3JXLORh-q_D5-zn9DcRJ1nq |
| linkProvider | Directory of Open Access Journals |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Spatial+patterns+of+brain+lesions+assessed+through+covariance+estimations+of+lesional+voxels+in+multiple+Sclerosis%3A+The+SPACE-MS+technique&rft.jtitle=NeuroImage+clinical&rft.au=Tur%2C+Carmen&rft.au=Grussu%2C+Francesco&rft.au=De+Angelis%2C+Floriana&rft.au=Prados%2C+Ferran&rft.date=2022-01-01&rft.issn=2213-1582&rft.eissn=2213-1582&rft.volume=33&rft.spage=102904&rft_id=info:doi/10.1016%2Fj.nicl.2021.102904&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_nicl_2021_102904 |
| thumbnail_m | http://cvtisr.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fcdn.clinicalkey.com%2Fck-thumbnails%2F22131582%2FS2213158221X00058%2Fcov150h.gif |