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Thalamic atrophy in multiple sclerosis: A magnetic resonance imaging marker of neurodegeneration throughout disease
Open accessAbstract
Objective: Thalamic volume is a candidate magnetic resonance imaging (MRI)‐based marker associated with neurodegeneration to hasten development of neuroprotective treatments. Our objective is to describe the longitudinal evolution of thalamic atrophy in MS and normal aging, and to estimate sample sizes for study design. Methods: Six hundred one subjects (2,632 MRI scans) were analyzed. Five hundred twenty subjects with relapse‐onset MS (clinically isolated syndrome, n = 90; relapsing–remitting MS, n = 392; secondary progressive MS, n = 38) underwent annual standardized 3T MRI scans for an average of 4.1 years, including a 1mm 3 3‐dimensional T1‐weighted sequence (3DT1; 2,485 MRI scans). Eighty‐one healthy controls (HC) were scanned longitudinally on the same scanner using the same protocol (147 MRI scans). 3DT1s were processed using FreeSurfer's longitudinal pipeline after lesion inpainting. Rates of normalized thalamic volume loss in MS and HC were compared in linear mixed effects models. Simulation‐based sample size calculations were performed incorporating the rate of atrophy in HC. Results: Thalamic volume declined significantly faster in MS subjects compared to HC, with an estimated decline of −0.71% per year (95% confidence interval [CI] = −0.77% to −0.64%) in MS subjects and −0.28% per year (95% CI = −0.58% to 0.02%) in HC (p for difference = 0.007). The rate of decline was consistent throughout the MS disease duration and across MS clinical subtypes. Eighty or 100 subjects per arm (α = 0.1 or 0.05, respectively) would be needed to detect the maximal effect size with 80% power in a 24‐month study. Interpretation: Thalamic atrophy occurs early and consistently throughout MS. Preliminary sample size calculations appear feasible, adding to its appeal as an MRI marker associated with neurodegeneration. Ann Neurol 2018;83:223–234
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Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS)
Kurtzke, J. F. (1983) · Neurology · doi:10.1212/wnl.33.11.1444 · Cited by 15,011
Axonal transection in the lesions of multiple sclerosis
Trapp, B. D., Peterson, J., Ransohoff, R. M., Rudick, R., Mörk, S., & Bö, L. (1998) · New England Journal of Medicine · doi:10.1056/nejm199801293380502 · Cited by 4,029
B-cell depletion with rituximab in relapsing-remitting multiple sclerosis
Hauser, S. L., Waubant, E., Arnold, D. L., Vollmer, T., Antel, J., Fox, R. J., Bar-Or, A., Panzara, M., Sarkar, N., Agarwal, S., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0706383 · Cited by 2,439
Self-citationUsing SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models
Singer, J. D. (1998) · Journal of Educational and Behavioral Statistics · doi:10.2307/1165280 · Cited by 1,092
Bjartmar, C., Wujek, J. R., & Trapp, B. D. (2003) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(02)00069-2 · Cited by 573
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Eitel, F., Soehler, E., Bellmann-Strobl, J., Brandt, A. U., Ruprecht, K., Giess, R. M., Kuchling, J., Asseyer, S., Weygandt, M., Haynes, J.-D., et al. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.102003 · Cited by 171
Mechanisms of Neurodegeneration and Axonal Dysfunction in Progressive Multiple Sclerosis
Correale, J., Marrodan, M., & Ysrraelit, M. C. (2019) · Biomedicines · doi:10.3390/biomedicines7010014 · Cited by 167
Misin, O., Matilainen, M., Nylund, M., Honkonen, E., Rissanen, E., Sucksdorff, M., & Airas, L. (2022) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000001182 · Cited by 24
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Metadata
- Authors
- Azevedo, C. J., Cen, S. Y., Khadka, S., Liu, S., Kornak, J., Shi, Y., Zheng, L., Hauser, S. L., & Pelletier, D.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2018-02
- Volume
- 83
- Issue
- 2
- Pages
- 223-234
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2783943799
- Cited by
- 250
- References
- 5
- FWCI
- 15.27
- Type
- journal article
- Language
- en
- Open access
- green
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