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A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis

Authors :
Antonio Cerdán Cerdá
Nicola Toschi
Constantina A Treaba
Valeria Barletta
Elena Herranz
Ambica Mehndiratta
Jose A Gomez-Sanchez
Caterina Mainero
Silvia De Santis
Source :
eLife, Vol 13 (2024)
Publication Year :
2024
Publisher :
eLife Sciences Publications Ltd, 2024.

Abstract

Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.

Details

Language :
English
ISSN :
2050084X
Volume :
13
Database :
Directory of Open Access Journals
Journal :
eLife
Publication Type :
Academic Journal
Accession number :
edsdoj.49c0b83f64f4edf93094eca8ae51567
Document Type :
article
Full Text :
https://doi.org/10.7554/eLife.79169