9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Longitudinal diffusion tensor magnetic resonance imaging analysis at the cohort level reveals disturbed cortical and callosal microstructure with spared corticospinal tract in the TDP-43 G298S ALS mouse model

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          In vivo diffusion tensor imaging (DTI) of the mouse brain was used to identify TDP-43 associated alterations in a mouse model for amyotrophic lateral sclerosis (ALS).

          Methods

          Ten mice with TDP-43 G298S overexpression under control of the Thy1.2 promoter and 10 wild type ( wt) underwent longitudinal DTI scans at 11.7 T, including one baseline and one follow-up scan with an interval of about 5 months. Whole brain-based spatial statistics (WBSS) of DTI-based parameter maps was used to identify longitudinal alterations of TDP-43 G298S mice compared to wt at the cohort level. Results were supplemented by tractwise fractional anisotropy statistics (TFAS) and histological evaluation of motor cortex for signs of neuronal loss.

          Results

          Alterations at the cohort level in TDP-43 G298S mice were observed cross-sectionally and longitudinally in motor areas M1/M2 and in transcallosal fibers but not in the corticospinal tract. Neuronal loss in layer V of motor cortex was detected in TDP-43 G298S at the later (but not at the earlier) timepoint compared to wt.

          Conclusion

          DTI mapping of TDP-43 G298S mice demonstrated progression in motor areas M1/M2. WBSS and TFAS are useful techniques to localize TDP-43 G298S associated alterations over time in this ALS mouse model, as a biological marker.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: not found

          A mesoscale connectome of the mouse brain.

          Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Diffusion tensor imaging analysis of sequential spreading of disease in amyotrophic lateral sclerosis confirms patterns of TDP-43 pathology.

            Diffusion tensor imaging can identify amyotrophic lateral sclerosis-associated patterns of brain alterations at the group level. Recently, a neuropathological staging system for amyotrophic lateral sclerosis has shown that amyotrophic lateral sclerosis may disseminate in a sequential regional pattern during four disease stages. The objective of the present study was to apply a new methodological diffusion tensor imaging-based approach to automatically analyse in vivo the fibre tracts that are prone to be involved at each neuropathological stage of amyotrophic lateral sclerosis. Two data samples, consisting of 130 diffusion tensor imaging data sets acquired at 1.5 T from 78 patients with amyotrophic lateral sclerosis and 52 control subjects; and 55 diffusion-tensor imaging data sets at 3.0 T from 33 patients with amyotrophic lateral sclerosis and 22 control subjects, were analysed by a tract of interest-based fibre tracking approach to analyse five tracts that become involved during the course of amyotrophic lateral sclerosis: the corticospinal tract (stage 1); the corticorubral and the corticopontine tracts (stage 2); the corticostriatal pathway (stage 3); the proximal portion of the perforant path (stage 4); and two reference pathways. The statistical analyses of tracts of interest showed differences between patients with amyotrophic lateral sclerosis and control subjects for all tracts. The significance level of the comparisons at the group level was lower, the higher the disease stage with corresponding involved fibre tracts. Both the clinical phenotype as assessed by the amyotrophic lateral sclerosis functional rating scale-revised and disease duration correlated significantly with the resulting staging scheme. In summary, the tract of interest-based technique allowed for individual analysis of predefined tract structures, thus making it possible to image in vivo the disease stages in amyotrophic lateral sclerosis. This approach can be used not only for individual clinical work-up purposes, but enlarges the spectrum of potential non-invasive surrogate markers as a neuroimaging-based read-out for amyotrophic lateral sclerosis studies within a clinical context. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The optimal trackability threshold of fractional anisotropy for diffusion tensor tractography of the corticospinal tract.

              In order to ensure that three-dimensional diffusion tensor tractography (3D-DTT) of the corticospinal tract (CST), is performed accurately and efficiently, we set out to find the optimal lower threshold of fractional anisotropy (FA) below which tract elongation is terminated (trackability threshold). Thirteen patients with acute or early subacute ischemic stroke causing motor deficits were enrolled in this study. We performed 3D-DTT of the CST with diffusion tensor MR (magnetic resonance) imaging. We segmented the CST and established a cross-section of the CST in a transaxial plane as a region of interest. Thus, we selectively measured the FA values of the right and left corticospinal tracts at the level of the cerebral peduncle, the posterior limb of the internal capsule, and the centrum semiovale. The FA values of the CST were also measured on the affected side at the level where the clinically relevant infarction was present in isotropic diffusion-weighted imaging. 3D-DTT allowed us to selectively measure the FA values of the CST. Among the 267 regions of interest we measured, the minimum FA value was 0.22. The FA values of the CST were smaller and more variable in the centrum semiovale than in the other regions. The mean minus twice the standard deviation of the FA values of the CST in the centrum semiovale was calculated at 0.22 on the normal unaffected side and 0.16 on the affected side. An FA value of about 0.20 was found to be the optimal trackability threshold.
                Bookmark

                Author and article information

                Contributors
                +49-731-177-1206 , hans-peter.mueller@uni-ulm.de
                david.brenner@uni-ulm.de
                francesco.roselli@uni-ulm.de
                diana.wiesner@uni-ulm.de
                alireza.abaei@uni-ulm.de
                martin.gorges@uni-ulm.de
                karin.danzer@uni-ulm.de
                albert.ludolph@rku.de
                tsao@jhmi.edu
                wong@jhmi.edu
                volker.rasche@uni-ulm.de
                jochen.weishaupt@uni-ulm.de
                jan.kassubek@uni-ulm.de
                Journal
                Transl Neurodegener
                Transl Neurodegener
                Translational Neurodegeneration
                BioMed Central (London )
                2047-9158
                30 August 2019
                30 August 2019
                2019
                : 8
                : 27
                Affiliations
                [1 ]ISNI 0000 0004 1936 9748, GRID grid.6582.9, Department of Neurology, , University of Ulm, ; Oberer Eselsberg 45, RKU, D-89081 Ulm, Germany
                [2 ]ISNI 0000 0004 0438 0426, GRID grid.424247.3, German Center for Neurodegenerative Diseases (DZNE), ; Ulm, Germany
                [3 ]ISNI 0000 0004 1936 9748, GRID grid.6582.9, Core Facility Small Animal MRI, , University of Ulm, ; Ulm, Germany
                [4 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Pathology, , The Johns Hopkins University School of Medicine, ; Baltimore, USA
                Article
                163
                10.1186/s40035-019-0163-y
                6716821
                25a97926-3b04-4bc8-b9d3-71f0d3f62a9c
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 November 2018
                : 16 July 2019
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Neurosciences
                diffusion tensor imaging,amyotrophic lateral sclerosis,mutant tdp-43,fiber tracking,mouse brain

                Comments

                Comment on this article