Voxel-Based MRI Intensitometry Reveals Extent of Cerebral White Matter Pathology in Amyotrophic Lateral Sclerosis
2014 | journal article. A publication with affiliation to the University of Göttingen.
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Hartung, V., Prell, T., Gaser, C., Turner, M. R., Tietz, F., Ilse, B., Bokemeyer, M. ... Grosskreutz, J. (2014). Voxel-Based MRI Intensitometry Reveals Extent of Cerebral White Matter Pathology in Amyotrophic Lateral Sclerosis. PLoS ONE, 9(8), Article e104894. doi: https://doi.org/10.1371/journal.pone.0104894
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- Authors
- Hartung, Viktor; Prell, Tino; Gaser, Christian; Turner, Martin R.; Tietz, Florian; Ilse, Benjamin; Bokemeyer, Martin; Witte, Otto-Wilhelm; Grosskreutz, Julian
- Abstract
- Amyotrophic lateral sclerosis (ALS) is characterized by progressive loss of upper and lower motor neurons. Advanced MRI techniques such as diffusion tensor imaging have shown great potential in capturing a common white matter pathology. However the sensitivity is variable and diffusion tensor imaging is not yet applicable to the routine clinical environment. Voxel-based morphometry (VBM) has revealed grey matter changes in ALS, but the bias-reducing algorithms inherent to traditional VBM are not optimized for the assessment of the white matter changes. We have developed a novel approach to white matter analysis, namely voxel-based intensitometry (VBI). High resolution T1-weighted MRI was acquired at 1.5 Tesla in 30 ALS patients and 37 age-matched healthy controls. VBI analysis at the group level revealed widespread white matter intensity increases in the corticospinal tracts, corpus callosum, sub-central, frontal and occipital white matter tracts and cerebellum. VBI results correlated with disease severity (ALSFRS-R) and patterns of cerebral involvement differed between bulbar- and limb-onset. VBI would be easily translatable to the routine clinical environment, and once optimized for individual analysis offers significant biomarker potential in ALS.
- Issue Date
- 2014
- Status
- published
- Publisher
- Public Library Science
- Journal
- PLoS ONE
- ISSN
- 1932-6203