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Longitudinal tracking of axonal loss using diffusion magnetic resonance imaging in multiple sclerosis.
Boonstra, Frederique M; Clough, Meaghan; Strik, Myrte; van der Walt, Anneke; Butzkueven, Helmut; White, Owen B; Law, Meng; Fielding, Joanne; Kolbe, Scott C.
Afiliação
  • Boonstra FM; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • Clough M; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • Strik M; Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia.
  • van der Walt A; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • Butzkueven H; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • White OB; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • Law M; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
  • Fielding J; Department Radiology, Alfred Health, Prahran 3005, Australia.
  • Kolbe SC; Department of Neuroscience, Central Clinical School, Monash University, Level 6, 99 Commercial Rd, Prahran 3005, Australia.
Brain Commun ; 4(2): fcac065, 2022.
Article em En | MEDLINE | ID: mdl-35425898
ABSTRACT
Axonal loss in the CNS is a key driver of progressive neurological impairments in people with multiple sclerosis. Currently, there are no established methods for tracking axonal loss clinically. This study aimed to determine the sensitivity of longitudinal diffusion MRI-derived fibre-specific measures of axonal loss in people with multiple sclerosis. Fibre measures were derived from diffusion MRI acquired as part of a standard radiological MRI protocol and were compared (i) to establish measures of neuro-axonal degeneration brain parenchymal fraction and retinal nerve fibre layer thickness and (ii) between different disease stages clinically isolated syndrome and early/late relapsing-remitting multiple sclerosis. Retrospectively identified data from 59 people with multiple sclerosis (18 clinically isolated syndrome, 22 early and 19 late relapsing-remitting) who underwent diffusion MRI as part of their routine clinical monitoring were collated and analysed. Twenty-six patients had 1-year and 14 patients had a 2-year follow-up. Brain parenchymal fraction was calculated from 3D MRI scans, and fibre-specific measures were calculated from diffusion MRI using multi-tissue constrained spherical deconvolution. At each study visit, patients underwent optical coherence tomography to determine retinal nerve fibre layer thickness, and standard neurological assessment expanded the disability status scale. We found a significant annual fibre-specific neuro-axonal degeneration (mean ± SD = -3.49 ± 3.32%, P < 0.001) that was ∼7 times larger than the annual change of brain parenchymal fraction (-0.53 ± 0.95%, P < 0.001), and more than four times larger than annual retinal nerve fibre layer thinning (-0.75 ± 2.50% P = 0.036). Only fibre-specific measures showed a significant difference in annual degeneration between the disease stages (P = 0.029). Reduced brain parenchymal fraction, retinal nerve fibre layer thickness and fibre-specific measures were moderately related to higher expanded disability status scale (rho = -0.368, rho = -0.408 and rho = -0.365, respectively). Fibre-specific measures can be measured from data collected within a standard radiological multiple sclerosis study and are substantially more sensitive to longitudinal change compared with brain atrophy and retinal nerve fibre layer thinning.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Brain Commun Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Brain Commun Ano de publicação: 2022 Tipo de documento: Article