From micro- to macro-structures in multiple sclerosis: what is the added value of diffusion imaging.

Cercignani, Mara ORCID: https://orcid.org/0000-0002-4550-2456 and Wheeler-Kingshott, Claudia Gandini 2019. From micro- to macro-structures in multiple sclerosis: what is the added value of diffusion imaging. NMR in Biomedicine 32 (4) , e3888. 10.1002/nbm.3888

Full text not available from this repository.

Abstract

Diffusion imaging has been instrumental in understanding damage to the central nervous system as a result of its sensitivity to microstructural changes. Clinical applications of diffusion imaging have grown exponentially over the past couple of decades in many neurological and neurodegenerative diseases, such as multiple sclerosis (MS). For several reasons, MS has been extensively researched using advanced neuroimaging techniques, which makes it an 'example disease' to illustrate the potential of diffusion imaging for clinical applications. In addition, MS pathology is characterized by several key processes competing with each other, such as inflammation, demyelination, remyelination, gliosis and axonal loss, enabling the specificity of diffusion to be challenged. In this review, we describe how diffusion imaging can be exploited to investigate micro-, meso- and macro-scale properties of the brain structure and discuss how they are affected by different pathological substrates. Conclusions from the literature are that larger studies are needed to confirm the exciting results from initial investigations before current trends in diffusion imaging can be translated to the neurology clinic. Also, for a comprehensive understanding of pathological processes, it is essential to take a multiple-level approach, in which information at the micro-, meso- and macroscopic scales is fully integrated.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Psychology Cardiff University Brain Research Imaging Centre (CUBRIC)
Publisher:	Wiley
ISSN:	0952-3480
Date of Acceptance:	25 November 2017
Last Modified:	09 Nov 2022 10:28
URI:	https://orca.cardiff.ac.uk/id/eprint/139580

Citation Data

Cited 33 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item