Literature DB >> 35397753

Advanced diffusion-weighted imaging models better characterize white matter neurodegeneration and clinical outcomes in multiple sclerosis.

Loredana Storelli1, Elisabetta Pagani1, Alessandro Meani1, Paolo Preziosa1,2, Massimo Filippi1,2,3,4,5, Maria A Rocca6,7,8.   

Abstract

BACKGROUND: White matter (WM) atrophy is relevant in multiple sclerosis (MS), but the methods of analysis currently used are not specific for microstructural changes. The aims of this study were to assess the use of advanced diffusion-weighted imaging (DWI) techniques proposed as measures of baseline and longitudinal WM atrophy in MS and to analyze whether these measures helped explain MS clinical disability (including cognitive impairment) better than volumetric and diffusion tensor (DT)-derived measures.
METHODS: 3DT1-weighted and DWI sequences were applied to 86 MS and 55 healthy controls (HC) at baseline and after one-year. Intra-cellular volume (vic) maps were computed from neurite orientation dispersion and density imaging model. Voxel-wise fiber-bundle cross-section (FCS) atrophy in MS compared to HC was estimated. Maps of fractional anisotropy and mean diffusivity were also obtained from DWI for a comparison with the proposed advanced DW-derived measures (vic and FCS).
RESULTS: Both at baseline and after 1-year, only FCS measure showed a significant atrophy in relapsing-remitting (RR) MS compared to HC and in progressive MS compared to RRMS, mainly located in specific WM tracts (corticospinal tract, splenium of the corpus callosum, left optic radiation, bilateral cingulum, middle cerebellar peduncle and anterior commissure, p value < 0.05). Global baseline FCS and vic were the selected predictors of clinical (R-sq = 0.33, p = 0.007) and cognitive scores (R-sq = 0.29, p = 0.0014) in a linear regression model.
CONCLUSION: Voxel-based FCS was able to detect WM tracts atrophy in MS clinical phenotypes with greater anatomical specificity compared to other measures (volumetric and DT-derived measures of WM damage). FCS and vic measured at baseline in the WM were the best predictors of clinical disability and cognitive impairment.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.

Entities:  

Keywords:  Diffusion-weighted imaging; Magnetic resonance imaging; Multiple sclerosis; White matter atrophy

Mesh:

Year:  2022        PMID: 35397753     DOI: 10.1007/s00415-022-11104-z

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   6.682


  41 in total

1.  NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain.

Authors:  Hui Zhang; Torben Schneider; Claudia A Wheeler-Kingshott; Daniel C Alexander
Journal:  Neuroimage       Date:  2012-03-30       Impact factor: 6.556

2.  Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution.

Authors:  J-Donald Tournier; Fernando Calamante; David G Gadian; Alan Connelly
Journal:  Neuroimage       Date:  2004-11       Impact factor: 6.556

3.  Informed constrained spherical deconvolution (iCSD).

Authors:  Timo Roine; Ben Jeurissen; Daniele Perrone; Jan Aelterman; Wilfried Philips; Alexander Leemans; Jan Sijbers
Journal:  Med Image Anal       Date:  2015-01-14       Impact factor: 8.545

4.  Reduced neurite density in the brain and cervical spinal cord in relapsing-remitting multiple sclerosis: A NODDI study.

Authors:  Sara Collorone; Niamh Cawley; Francesco Grussu; Ferran Prados; Francesca Tona; Alberto Calvi; Baris Kanber; Torben Schneider; Lucas Kipp; Hui Zhang; Daniel C Alexander; Alan J Thompson; Ahmed Toosy; Claudia Am Gandini Wheeler-Kingshott; Olga Ciccarelli
Journal:  Mult Scler       Date:  2019-11-04       Impact factor: 6.312

5.  Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data.

Authors:  Ben Jeurissen; Jacques-Donald Tournier; Thijs Dhollander; Alan Connelly; Jan Sijbers
Journal:  Neuroimage       Date:  2014-08-07       Impact factor: 6.556

6.  In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis.

Authors:  Tobias Granberg; Qiuyun Fan; Constantina Andrada Treaba; Russell Ouellette; Elena Herranz; Gabriel Mangeat; Céline Louapre; Julien Cohen-Adad; Eric C Klawiter; Jacob A Sloane; Caterina Mainero
Journal:  Brain       Date:  2017-11-01       Impact factor: 13.501

7.  Brain microstructural and metabolic alterations detected in vivo at onset of the first demyelinating event.

Authors:  Sara Collorone; Ferran Prados; Baris Kanber; Niamh M Cawley; Carmen Tur; Francesco Grussu; Bhavana S Solanky; Marios Yiannakas; Indran Davagnanam; Claudia A M Gandini Wheeler-Kingshott; Frederik Barkhof; Olga Ciccarelli; Ahmed T Toosy
Journal:  Brain       Date:  2021-06-22       Impact factor: 13.501

8.  Investigating white matter fibre density and morphology using fixel-based analysis.

Authors:  David A Raffelt; J-Donald Tournier; Robert E Smith; David N Vaughan; Graeme Jackson; Gerard R Ridgway; Alan Connelly
Journal:  Neuroimage       Date:  2016-09-14       Impact factor: 6.556

9.  Axonal loss in major sensorimotor tracts is associated with impaired motor performance in minimally disabled multiple sclerosis patients.

Authors:  Myrte Strik; L Eduardo Cofré Lizama; Camille J Shanahan; Anneke van der Walt; Frederique M C Boonstra; Rebecca Glarin; Trevor J Kilpatrick; Jeroen J G Geurts; Jon O Cleary; Menno M Schoonheim; Mary P Galea; Scott C Kolbe
Journal:  Brain Commun       Date:  2021-03-16

10.  Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Authors:  Francesco Grussu; Torben Schneider; Carmen Tur; Richard L Yates; Mohamed Tachrount; Andrada Ianuş; Marios C Yiannakas; Jia Newcombe; Hui Zhang; Daniel C Alexander; Gabriele C DeLuca; Claudia A M Gandini Wheeler-Kingshott
Journal:  Ann Clin Transl Neurol       Date:  2017-08-15       Impact factor: 4.511

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