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Cervical spinal cord susceptibility-weighted MRI at 7T: Application to multiple sclerosis
- Source :
- NeuroImage, Vol 284, Iss , Pp 120460- (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- Background: Susceptibility-weighted imaging (SWI) has been extensively studied in the brain and in diseases of the central nervous system such as multiple sclerosis (MS) providing unique opportunities to visualize cerebral vasculature and disease-related pathology, including the central vein sign (CVS) and paramagnetic rim lesions (PRLs). However, similar studies evaluating SWI in the spinal cord of patients with MS remain severely limited. Purpose: Based on our previous findings of enlarged spinal vessels in MS compared to healthy controls (HCs), we developed high-field SWI acquisition and processing methods for the cervical spinal cord with application in people with MS (pwMS) and HCs. Here, we demonstrate the vascular variability between the two cohorts and unique MS lesion features in the cervical cord. Methods: In this retrospective, exploratory pilot study conducted between March 2021 and March 2022, we scanned 12 HCs and 9 pwMS using an optimized non-contrast 2D T2*-weighted gradient echo sequence at 7 tesla. The overall appearance of the white and gray matter as well as tissue vasculature were compared between the two cohorts and areas of MS pathology in the patient group were assessed using both the magnitude and processed SWI images. Results: We show improved visibility of vessels and more pronounced gray and white matter contrast in the MS group compared to HCs, hypointensities surrounding the cord in the MS cohort, and identify signal changes indicative of the CVS and paramagnetic rims in 66 % of pwMS with cervical spinal lesions. Conclusion: In this first study of SWI at 7T in the human spinal cord, SWI holds promise in advancing our understanding of disease processes in the cervical cord in MS.
Details
- Language :
- English
- ISSN :
- 10959572
- Volume :
- 284
- Issue :
- 120460-
- Database :
- Directory of Open Access Journals
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9b02c43dc4ff42d29dbaffddfd108560
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2023.120460