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  Disentangling brain functional network remodeling in corticobasal syndrome: A multimodal MRI study

Ballarini, T., Albrecht, F., Mueller, K., Jech, R., Diehl-Schmid, J., Fliessbach, K., et al. (2020). Disentangling brain functional network remodeling in corticobasal syndrome: A multimodal MRI study. NeuroImage: Clinical, 25: 102112. doi:10.1016/j.nicl.2019.102112.

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Ballarini, Tommaso1, Author              
Albrecht, Franziska1, Author              
Mueller, Karsten2, Author              
Jech , Robert3, Author
Diehl-Schmid, Janine4, Author
Fliessbach, Klaus5, Author
Kassubek, Jan6, Author
Lauer, Martin7, Author
Fassbender, Klaus8, Author
Schneider, Anja5, Author
Synofzik, Matthis9, 10, Author
Wiltfang, Jens11, Author
FTLD Consortium, Author              
Otto, Markus6, Author
Schroeter, Matthias L.1, 12, Author              
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              
3Department of Neurology, Charité University Medicine Berlin, Germany, ou_persistent22              
4Department of Psychiatry and Psychotherapy, TU Munich, Germany, ou_persistent22              
5Department of Neurodegenerative Disease and Geriatric Psychiatry, University Hospital Bonn, Germany, ou_persistent22              
6Department of Neurology, Ulm University, Germany, ou_persistent22              
7Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Germany, ou_persistent22              
8Clinic for Neurology, Saarland University, Germany, ou_persistent22              
9Hertie-Institute for Clinical Brain Research, Eberhard Karls University Tübingen, Germany, ou_persistent22              
10German Center for Neurodegenerative Diseases, Tübingen, Germany, ou_persistent22              
11University Medical Center, Göttingen, Germany, ou_persistent22              
12Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              


Free keywords: Corticobasal syndrome; Imaging biomarkers; Magnetic resonance imaging; Resting-state functional connectivity; Voxel-based morphometry; Support vector machine
 Abstract: Objective The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimodal T1-weighted and resting-state functional magnetic resonance imaging (MRI). Methods Nineteen patients with CBS (age 67.0 ± 6.0 years; mean±SD) and 19 matched controls (66.5 ± 6.0) were enrolled from the German Frontotemporal Lobar Degeneration Consortium. Changes in functional connectivity and structure were respectively assessed with eigenvector centrality mapping complemented by seed-based analysis and with voxel-based morphometry. In addition to mass-univariate statistics, multivariate support vector machine (SVM) classification tested the potential of multimodal MRI to differentiate patients and controls. External validity of SVM was assessed on independent CBS data from the 4RTNI database. Results A decrease in brain interconnectedness was observed in the right central operculum, middle temporal gyrus and posterior insula, while widespread connectivity increases were found in the anterior cingulum, medial superior-frontal gyrus and in the bilateral caudate nuclei. Severe and diffuse gray matter volume reduction, especially in the bilateral insula, putamen and thalamus, characterized CBS. SVM classification revealed that both connectivity (area under the curve 0.81) and structural abnormalities (0.80) distinguished CBS from controls, while their combination led to statistically non-significant improvement in discrimination power, questioning the additional value of functional connectivity over atrophy. SVM analyses based on structural MRI generalized moderately well to new data, which was decisively improved when guided by meta-analytically derived disease-specific regions-of-interest. Conclusions Our data-driven results show impairment of functional connectivity and brain structure in CBS and explore their potential as imaging biomarkers.


Language(s): eng - English
 Dates: 2019-11-272019-08-092019-12-012019-12-022020
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.nicl.2019.102112
Other: Epub ahead of print
PMID: 31821953
 Degree: -



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Project name : -
Grant ID : O1GI1007A
Funding program : German Consortium for Frontotemporal Lobar Degeneration
Funding organization : German Federal Ministry of Education and Research (BMBF)
Project name : -
Grant ID : PDF-IRG-1307
Funding program : -
Funding organization : Parkinson's Disease Foundation
Project name : -
Grant ID : 11362
Funding program : -
Funding organization : Michael Fox Foundation
Project name : -
Grant ID : SCHR 774/5-1
Funding program : -
Funding organization : German Research Foundation (DFG)
Project name : -
Grant ID : 16-13323
Funding program : -
Funding organization : Czech Science Foundation GAČR
Project name : Czech Republic Progres Q27/LF1
Grant ID : -
Funding program : -
Funding organization : Charles University
Project name : -
Grant ID : R01 AG038791
Funding program : National Institutes of Health Grant
Funding organization : 4-Repeat Tauopathy Neuroimaging Initiative
Project name : -
Grant ID : -
Funding program : -
Funding organization : Tau Research Consortium

Source 1

Title: NeuroImage: Clinical
Source Genre: Journal
Publ. Info: Elsevier
Pages: - Volume / Issue: 25 Sequence Number: 102112 Start / End Page: - Identifier: ISSN: 2213-1582
CoNE: https://pure.mpg.de/cone/journals/resource/2213-1582