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Longitudinal Diffusion Tensor Imaging-Based Assessment of Tract Alterations: An Application to Amyotrophic Lateral Sclerosis

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TLDR
On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration, and this finding was demonstrated here for ALS as a fast progressing Neurodegenerative disease.
Abstract
Objective: The potential of magnetic resonance imaging (MRI) as a technical biomarker for cerebral microstructural alterations in neurodegenerative diseases is under investigation. In this study, a framework for the longitudinal analysis of diffusion tensor imaging (DTI)-based mapping was applied to the assessment of predefined white matter tracts in amyotrophic lateral sclerosis (ALS), as an example for a rapid progressive neurodegenerative disease. Methods: DTI was performed every 3 months in six patients with ALS (mean (M) = 7.7; range 3 to 15 scans) and in six controls (M = 3; range 2-5 scans) with the identical scanning protocol, resulting in a total of 65 longitudinal DTI datasets. Fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD), and the ratio AD/RD were studied to analyze alterations within the corticospinal tract (CST) which is a prominently affected tract structure in ALS and the tract correlating with Braak's neuropathological stage 1. A correlation analysis was performed between progression rates based on DTI metrics and the revised ALS functional rating scale (ALS-FRS-R). Results: Patients with ALS showed an FA and AD/RD decline along the CST, while DTI metrics of controls did not change in longitudinal DTI scans. The FA and AD/RD decrease progression correlated significantly with ALS-FRS-R decrease progression. Conclusion: On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration. This finding was demonstrated here for ALS as a fast progressing neurodegenerative disease.

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Connectome-Based Propagation Model in Amyotrophic Lateral Sclerosis.

TL;DR: To simulate disease propagation using network analyses of cerebral magnetic resonance imaging (MRI) data to predict disease progression, a simulation of amyotrophic lateral sclerosis (ALS) is conducted.
References
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Journal ArticleDOI

Neuropathological stageing of Alzheimer-related changes.

Heiko Braak, +1 more
TL;DR: The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations, permitting the differentiation of six stages.
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Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

TL;DR: TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies by solving the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis.
Journal ArticleDOI

Thresholding of statistical maps in functional neuroimaging using the false discovery rate.

TL;DR: This paper introduces to the neuroscience literature statistical procedures for controlling the false discovery rate (FDR) and demonstrates this approach using both simulations and functional magnetic resonance imaging data from two simple experiments.
Journal ArticleDOI

Diffusion tensor imaging: Concepts and applications

TL;DR: The concepts behind diffusion tensor imaging are reviewed and potential applications, including fiber tracking in the brain, which, in combination with functional MRI, might open a window on the important issue of connectivity.
Journal ArticleDOI

Toward a quantitative assessment of diffusion anisotropy

TL;DR: New indices calculated from the entire diffusion tensor are rotationally invariant (RI) and show that anisotropy is highly variable in different white matter regions depending on the degree of coherence of fiber tract directions.
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