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Multicontrast MRI quantification of focal inflammation and degeneration in multiple sclerosis

Bonnier, Guillaume and Roche, Alexis and Romascano, David and Simioni, Samanta and Meskaldji, Djalel-Eddine and Rotzinger, David and Lin, Ying-Chia and Menegaz, Gloria and Schluep, Myriam and Du Pasquier, Renaud and Sumpf, Tilman Johannes and Frahm, Jens and Thiran, Jean-Philippe and Krueger, Gunnar and Granziera, Cristina Multicontrast MRI quantification of focal inflammation and degeneration in multiple sclerosis. BioMed Research International, 25 (569123). pp. 1-10. ISSN 2314-6133 (2014)

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Abstract

Local microstructural pathology in multiple sclerosis patients might influence their clinical performance. This study applied multicontrast MRI to quantify inflammation and neurodegeneration in MS lesions. We explored the impact of MRI-based lesion pathology in cognition and disability. Methods. 36 relapsing-remitting MS subjects and 18 healthy controls underwent neurological, cognitive, behavioural examinations and 3 T MRI including (i) fluid attenuated inversion recovery, double inversion recovery, and magnetization-prepared gradient echo for lesion count; (ii) T1, T2, and T2* relaxometry and magnetisation transfer imaging for lesion tissue characterization. Lesions were classified according to the extent of inflammation/neurodegeneration. A generalized linear model assessed the contribution of lesion groups to clinical performances. Results. Four lesion groups were identified and characterized by (1) absence of significant alterations, (2) prevalent inflammation, (3) concomitant inflammation and microdegeneration, and (4) prevalent tissue loss. Groups 1, 3, 4 correlated with general disability (Adj-; ), executive function (Adj-; ), verbal memory (Adj-; ), and attention (Adj-; ). Conclusion. Multicontrast MRI provides a new approach to infer in vivo histopathology of plaques. Our results support evidence that neurodegeneration is the major determinant of patients’ disability and cognitive dysfunction

Item Type: Article
Identification Number: https://doi.org/10.1155/2015/569123
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 18 Dec 2014 12:15
Last Modified: 02 Nov 2015 11:27
URI: http://eprints.imtlucca.it/id/eprint/2425

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