The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Dynamic Imaging of Individual Remyelination Profiles in Multiple Sclerosis
Open accessAbstract
Background: Quantitative in vivo imaging of myelin loss and repair in patients with multiple sclerosis (MS) is essential to understand the pathogenesis of the disease and to evaluate promyelinating therapies. Selectively binding myelin in the central nervous system white matter, Pittsburgh compound B ([11 C]PiB) can be used as a positron emission tomography (PET) tracer to explore myelin dynamics in MS. Methods: Patients with active relapsing‐remitting MS (n = 20) and healthy controls (n = 8) were included in a longitudinal trial combining PET with [11 C]PiB and magnetic resonance imaging. Voxel‐wise maps of [11 C]PiB distribution volume ratio, reflecting myelin content, were derived. Three dynamic indices were calculated for each patient: the global index of myelin content change; the index of demyelination; and the index of remyelination. Results: At baseline, there was a progressive reduction in [11 C]PiB binding from the normal‐appearing white matter to MS lesions, reflecting a decline in myelin content. White matter lesions were characterized by a centripetal decrease in the tracer binding at the voxel level. During follow‐up, high between‐patient variability was found for all indices of myelin content change. Dynamic remyelination was inversely correlated with clinical disability (p = 0.006 and beta‐coefficient = –0.67 with the Expanded Disability Status Scale; p = 0.003 and beta‐coefficient = –0.68 with the MS Severity Scale), whereas no significant clinical correlation was found for the demyelination index. Interpretation: [11 C]PiB PET allows quantification of myelin dynamics in MS and enables stratification of patients depending on their individual remyelination potential, which significantly correlates with clinical disability. This technique should be considered to assess novel promyelinating drugs. Ann Neurol 2016;79:726–738
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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
Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria
Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., et al. (2011) · Annals of Neurology · doi:10.1002/ana.22366 · Cited by 9,802
Premyelinating Oligodendrocytes in Chronic Lesions of Multiple Sclerosis
Chang, A., Tourtellotte, W. W., Rudick, R., & Trapp, B. D. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa010994 · Cited by 991
Multiple sclerosis: risk factors, prodromes, and potential causal pathways
Ramagopalan, S. V., Dobson, R., Meier, U. C., & Giovannoni, G. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(10)70094-6 · Cited by 548
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Altered human oligodendrocyte heterogeneity in multiple sclerosis
Jäkel, S., Agirre, E., Mendanha Falcão, A., van Bruggen, D., Lee, K. W., Knuesel, I., Malhotra, D., ffrench-Constant, C., Williams, A., & Castelo-Branco, G. (2019) · Nature · doi:10.1038/s41586-019-0903-2 · Cited by 854
Myelin in the Central Nervous System: Structure, Function, and Pathology
Stadelmann, C., Timmler, S., Barrantes-Freer, A., & Simons, M. (2019) · Physiological Reviews · doi:10.1152/physrev.00031.2018 · Cited by 728
Multiple sclerosis progression: time for a new mechanism-driven framework
Kuhlmann, T., Moccia, M., Coetzee, T., Cohen, J. A., Correale, J., Graves, J., Marrie, R. A., Montalban, X., Yong, V. W., Thompson, A. J., et al. (2023) · The Lancet Neurology · doi:10.1016/s1474-4422(22)00289-7 · Cited by 667
Regenerating CNS myelin — from mechanisms to experimental medicines
Franklin, R. J. M., & ffrench-Constant, C. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.136 · Cited by 647
Remyelination in multiple sclerosis: From basic science to clinical translation
Lubetzki, C., Zalc, B., Williams, A., Stadelmann, C., & Stankoff, B. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30140-x · Cited by 350
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Metadata
- Authors
- Bodini, B., Veronese, M., García‐Lorenzo, D., Battaglini, M., Poirion, E., Chardain, A., Freeman, L., Louapre, C., Tchikviladze, M., Papeix, C., Dollé, F., Zalc, B., Lubetzki, C., Bottlaender, M., Turkheimer, F., & Stankoff, B.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2016-05
- Volume
- 79
- Issue
- 5
- Pages
- 726-738
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2280588432
- Cited by
- 240
- References
- 4
- FWCI
- 15.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Bodini, B., Veronese, M., García‐Lorenzo, D., Battaglini, M., Poirion, E., Chardain, A., Freeman, L., Louapre, C., Tchikviladze, M., Papeix, C., Dollé, F., Zalc, B., Lubetzki, C., Bottlaender, M., Turkheimer, F., & Stankoff, B. (2016). Dynamic Imaging of Individual Remyelination Profiles in Multiple Sclerosis. Annals of Neurology. https://doi.org/10.1002/ana.24620
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