Cortical Volume Loss and Neurologic Dysfunction in Multiple Sclerosis

2016 ◽  
Vol 73 (8) ◽  
pp. 910 ◽  
Author(s):  
Michael K. Racke ◽  
Jaime Imitola
2016 ◽  
Vol 26 (5) ◽  
pp. 532-538 ◽  
Author(s):  
Angela Vidal-Jordana ◽  
Jaume Sastre-Garriga ◽  
Francisco Pérez-Miralles ◽  
Deborah Pareto ◽  
Jordi Rio ◽  
...  

2021 ◽  
Vol 351 ◽  
pp. 577466
Author(s):  
Hiroaki Yokote ◽  
Shuta Toru ◽  
Yoichiro Nishida ◽  
Takaaki Hattori ◽  
Nobuo Sanjo ◽  
...  

2018 ◽  
Vol 90 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Maria Pia Sormani ◽  
Nicola De Stefano ◽  
Gavin Giovannoni ◽  
Dawn Langdon ◽  
Daniela Piani-Meier ◽  
...  

ObjectiveTo assess the prognostic value of practice effect on Paced Auditory Serial Addition Test (PASAT) in multiple sclerosis.MethodsWe compared screening (day −14) and baseline (day 0) PASAT scores of 1009 patients from the FTY720 Research Evaluating Effects of Daily Oral therapy in Multiple Sclerosis (FREEDOMS) trial. We grouped patients into high and low learners if their PASAT score change was above or below the median change in their screening PASAT quartile group. We used Wilcoxon test to compare baseline disease characteristics between high and low learners, and multiple regression models to assess the respective impact of learning ability, baseline normalised brain volume and treatment on brain volume loss and 6-month confirmed disability progression over 2 years.ResultsThe mean PASAT score at screening was 45.38, increasing on average by 3.18 from day −14 to day 0. High learners were younger (p=0.003), had lower Expanded Disability Status Scale score (p=0.031), higher brain volume (p<0.001) and lower T2 lesion volume (p=0.009) at baseline. Learning status was not significantly associated with disability progression (HR=0.953, p=0.779), when adjusting for baseline normalised brain volume, screening PASAT score and treatment arm. However, the effect of fingolimod on disability progression was more pronounced in high learners (HR=0.396, p<0.001) than in low learners (HR=0.798, p=0.351; p for interaction=0.05). Brain volume loss at month 24 tended to be higher in low learners (0.17%, p=0.058), after adjusting for the same covariates.ConclusionsShort-term practice effects on PASAT are related to brain volume, disease severity and age and have clinically meaningful prognostic implications. High learners benefited more from fingolimod treatment.


Neurology ◽  
2018 ◽  
Vol 91 (24) ◽  
pp. 1079-1080
Author(s):  
Ruth Ann Marrie ◽  
Helmut Butzkueven ◽  
Alberto Ascherio

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Emily Iannopollo ◽  
Ryan Plunkett ◽  
Kara Garcia

Background and Hypothesis: Magnetic resonance imaging (MRI) has become a useful tool in monitoring the progression of Alzheimer's disease. Previous surface-based analysis has focused on changes in cortical thickness associated with the disease1. The objective of this study is to analyze MRI-derived cortical reconstructions for patterns of atrophy in terms of both cortical thickness and cortical volume. We hypothesize that Alzheimer’s Disease progression will be associated with a more significant change in volume than thickness. Experimental Design or Project Methods: MRI data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). All subjects with baseline and two-year 3T MRI scans were included. Segmentation of MRIs into gray and white matter was performed with FreeSurfer2,3,4,5. Subjects whose scans did not segment accurately were excluded. Surfaces were then registered to a common atlas with Ciftify6, and anatomically-constrained Multimodal Surface Matching (aMSM) was used to analyze longitudinal changes in each subject7. This produced continuous surface maps showing changes in cortical surface area and thickness. These maps were multiplied to create cortical volume maps8. Permutation Analysis of Linear Models (PALM) was used to perform two-sample t-tests comparing the maps of the Alzheimer’s and control groups9. Results: Preliminary analysis of nine Alzheimer’s subjects and nine control subjects produced surface maps displaying patterns that were expected given previous research findings10,11. There was increased volume and thickness loss in Alzheimer’s subjects relative to controls, with relatively high loss in structures of the medial temporal lobe. Future analysis of a larger sample will determine whether statistically significant differences exist between the Alzheimer’s and control groups in terms of thickness loss and volume loss. Conclusion and Potential Impact: If significant results are found, surface-based analysis of cortical volume may allow for detection of atrophy at an earlier stage in disease progression than would be possible based on cortical thickness.   References 1. Clarkson MJ, Cardoso MJ, Ridgway GR, Modat M, Leung KK, Rohrer JD, Fox NC, Ourselin S. A comparison of voxel and surface based cortical thickness estimation methods. NeuroImage. 2011 Aug 1; 57(3):856-65. 2. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage. 1999;9:179194. 3. Fischl B, Sereno M, Dale A. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage. 1999;9:195–207.  4. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002;33:341-355. 5. Fischl B, Salat DH, van der Kouwe AJ, Makris N, Segonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage 2004;23 Suppl 1:S69-84. 6. Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, Xu J, Jbabdi S, Webster M, Polimeni JR, Van Essen DC, Jenkinson M, WU-Minn HCP Consortium. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013 Oct 15;80:105-24. 7. Robinson EC, Garcia K, Glasser MF, Chen Z, Coalson TS, Makropoulos A, Bozek J, Wright R, Schuh A, Webster M, Hutter J, Price A, Cordero Grande L, Hughes E, Tusor N, Bayly PV, Van Essen DC, Smith SM, Edwards AD, Hajnal J, Jenkinson M, Glocker B, Rueckert D. Multimodal surface matching with higher-order smoothness constraints. Neuroimage. 2018;167:453-65. 8. Marcus DS, Harwell J, Olsen T, Hodge M, Glasser MF, Prior F, Jenkinson M, Laumann T, Curtiss SW, Van Essen DC. Informatics and data mining tools and strategies for the human connectome project. Front Neuroinform 2011;5:4. 9. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. NeuroImage, 2014;92:381-397 10. Matsuda, H. MRI morphometry in Alzheimer’s disease. Ageing Research Reviews. 2016 Sep;30:17-24. 11. Risacher SL, Shen L, West JD, Kim S, McDonald BC, Beckett LA, Harvey DJ, Jack CR Jr, Weiner MW, Saykin AJ. Alzheimer's Disease Neuroimaging Initiative (ADNI). Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort. Neurobiol Aging. 2010 Aug;31(8):1401-18. 


2015 ◽  
Vol 21 (10) ◽  
pp. 1280-1290 ◽  
Author(s):  
V Popescu ◽  
R Klaver ◽  
P Voorn ◽  
Y Galis-de Graaf ◽  
DL Knol ◽  
...  

Background: Cortical atrophy, assessed with magnetic resonance imaging (MRI), is an important outcome measure in multiple sclerosis (MS) studies. However, the underlying histopathology of cortical volume measures is unknown. Objective: We investigated the histopathological substrate of MRI-measured cortical volume in MS using combined post-mortem imaging and histopathology. Methods: MS brain donors underwent post-mortem whole-brain in-situ MRI imaging. After MRI, tissue blocks were systematically sampled from the superior and inferior frontal gyrus, anterior cingulate gyrus, inferior parietal lobule, and superior temporal gyrus. Histopathological markers included neuronal, axonal, synapse, astrocyte, dendrite, myelin, and oligodendrocyte densities. Matched cortical volumes from the aforementioned anatomical regions were measured on the MRI, and used as outcomes in a nested prediction model. Results: Forty-five tissue blocks were sampled from 11 MS brain donors. Mean age at death was 68±12 years, post-mortem interval 4±1 hours, and disease duration 35±15 years. MRI-measured regional cortical volumes varied depending on anatomical region. Neuronal density, neuronal size, and axonal density were significant predictors of GM volume. Conclusions: In patients with long-standing disease, neuronal and axonal pathology are the predominant pathological substrates of MRI-measured cortical volume in chronic MS.


2020 ◽  
Vol 6 (1) ◽  
pp. 205521732090248
Author(s):  
Cecilie Jacobsen ◽  
Robert Zivadinov ◽  
Kjell-Morten Myhr ◽  
Turi O Dalaker ◽  
Ingvild Dalen ◽  
...  

Background Multiple sclerosis is often associated with unemployment. The contribution of grey matter atrophy to unemployment is unclear. Objectives To identify magnetic resonance imaging biomarkers of grey matter and clinical symptoms associated with unemployment in multiple sclerosis patients. Methods Demographic, clinical data and 1.5 T magnetic resonance imaging scans were collected in 81 patients at the time of inclusion and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. Statistical analysis was performed using a mixed linear model. Results At baseline 31 (38%) of the patients were unemployed, at 5-year follow-up 44 (59%) and at 10-year follow-up 34 (81%) were unemployed. The unemployed patients had significantly lower subcortical deep grey matter volume ( P < 0.001), specifically thalamus, pallidus, putamen and hippocampal volumes, and cortical volume ( P = 0.011); and significantly greater T1 ( P < 0.001)/T2 ( P < 0.001) lesion volume than the employed patient group at baseline. Subcortical deep grey matter volumes, and to a lesser degree cortical volume, were significantly associated with unemployment throughout the follow-up. Conclusion We found significantly greater atrophy of subcortical deep grey matter and cortical volume at baseline and during follow-up in the unemployed patient group. Atrophy of subcortical deep grey matter showed a stronger association to unemployment than atrophy of cortical volume during the follow-up.


Sign in / Sign up

Export Citation Format

Share Document