1. |
- Niemi, MEK, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
2. |
- Barletta, V, et al.
(author)
-
Quantitative 7-Tesla Imaging of Cortical Myelin Changes in Early Multiple Sclerosis
- 2021
-
In: Frontiers in neurology. - : Frontiers Media SA. - 1664-2295. ; 12, s. 714820-
-
Journal article (peer-reviewed)abstract
- Cortical demyelination occurs early in multiple sclerosis (MS) and relates to disease outcome. The brain cortex has endogenous propensity for remyelination as proven from histopathology study. In this study, we aimed at characterizing cortical microstructural abnormalities related to myelin content by applying a novel quantitative MRI technique in early MS. A combined myelin estimation (CME) cortical map was obtained from quantitative 7-Tesla (7T) T2* and T1 acquisitions in 25 patients with early MS and 19 healthy volunteers. Cortical lesions in MS patients were classified based on their myelin content by comparison with CME values in healthy controls as demyelinated, partially demyelinated, or non-demyelinated. At follow-up, we registered changes in cortical lesions as increased, decreased, or stable CME. Vertex-wise analysis compared cortical CME in the normal-appearing cortex in 25 MS patients vs. 19 healthy controls at baseline and investigated longitudinal changes at 1 year in 10 MS patients. Measurements from the neurite orientation dispersion and density imaging (NODDI) diffusion model were obtained to account for cortical neurite/dendrite loss at baseline and follow-up. Finally, CME maps were correlated with clinical metrics. CME was overall low in cortical lesions (p = 0.03) and several normal-appearing cortical areas (p < 0.05) in the absence of NODDI abnormalities. Individual cortical lesion analysis revealed, however, heterogeneous CME patterns from extensive to partial or absent demyelination. At follow-up, CME overall decreased in cortical lesions and non-lesioned cortex, with few areas showing an increase (p < 0.05). Cortical CME maps correlated with processing speed in several areas across the cortex. In conclusion, CME allows detection of cortical microstructural changes related to coexisting demyelination and remyelination since the early phases of MS, and shows to be more sensitive than NODDI and relates to cognitive performance.
|
|
3. |
- Mehndiratta, A, et al.
(author)
-
Characterization of thalamic lesions and their correlates in multiple sclerosis by ultra-high-field MRI
- 2021
-
In: Multiple sclerosis (Houndmills, Basingstoke, England). - : SAGE Publications. - 1477-0970 .- 1352-4585. ; 27:5, s. 674-683
-
Journal article (peer-reviewed)abstract
- Thalamic pathology is a marker for neurodegeneration and multiple sclerosis (MS) disease progression. Objective: To characterize (1) the morphology of thalamic lesions, (2) their relation to cortical and white matter (WM) lesions, and (3) clinical measures, and to assess (4) the imaging correlates of thalamic atrophy. Methods: A total of 90 MS patients and 44 healthy controls underwent acquisition of 7 Tesla images for lesion segmentation and 3 Tesla scans for atrophy evaluation. Thalamic lesions were classified according to the shape and the presence of a central venule. Regression analysis identified the predictors of (1) thalamic atrophy, (2) neurological disability, and (3) information processing speed. Results: Thalamic lesions were mostly ovoid than periventricular, and for the great majority (78%) displayed a central venule. Lesion volume in the thalamus, cortex, and WM did not correlate with each other. Thalamic atrophy was only associated with WM lesion volume ( p = 0.002); subpial and WM lesion volumes were associated with neurological disability ( p = 0.016; p < 0.001); and WM and thalamic lesion volumes were related with cognitive impairment ( p < 0.001; p = 0.03). Conclusion: Thalamic lesions are unrelated to those in the cortex and WM, suggesting that they may not share common pathogenic mechanisms and do not contribute to thalamic atrophy. Combined WM, subpial, and thalamic lesion volumes at 7 Tesla contribute to the disease severity.
|
|
4. |
|
|