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Front. Hum. Neurosci. | doi: 10.3389/fnhum.2017.00567

Longitudinal Diffusion Tensor Imaging-based assessment of tract alterations: an application to amyotrophic lateral sclerosis

  • 1Department of Neurology, University of Regensburg, Germany
  • 2University of Ulm, Germany

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 three months in six patients with ALS (mean(M)= 7.7; range 3 to15 scans) and in six controls (M= 3; range 2 to 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 analyse 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.

Keywords: fractional anisotropy, Magnetic Resonance Imaging, Diffusion Tensor Imaging, neurodegeneration, methods

Received: 08 Sep 2017; Accepted: 07 Nov 2017.

Edited by:

Peter Sörös, University of Oldenburg, Germany

Reviewed by:

Manoj K. Jaiswal, Icahn School of Medicine at Mount Sinai, United States
Alessia Sarica, Istituto di Bioimmagini e Fisiologia Molecolare (CNR), Italy  

Copyright: © 2017 Baldaranov, Khomenko, Kobor, Bogdahn, Kassubek and Müller. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Hans-Peter Müller, University of Ulm, Ulm, Germany,