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Autoren: Gonzalez-Escamilla, Gabriel
Muthuraman, Muthuraman
Reich, Martin
Koirala, Nabin
Riedel, Christian
Glaser, Martin
Lange, Florian
Deuschl, Günther
Volkmann, Jens
Groppa, Sergiu
Titel: Cortical network fingerprints predict deep brain stimulation outcome in dystonia
Online-Publikationsdatum: 21-Jun-2022
Erscheinungsdatum: 2019
Sprache des Dokuments: Englisch
Zusammenfassung/Abstract: BACKGROUND Deep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns. METHODS From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior-outcome group or moderate-outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray-matter fingerprints. RESULTS The moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray-matter atrophy patterns to predict DBS outcomes. CONCLUSIONS The analysis of cortical integrity, informed by group-level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS.
DDC-Sachgruppe: 610 Medizin
610 Medical sciences
Veröffentlichende Institution: Johannes Gutenberg-Universität Mainz
Organisationseinheit: FB 04 Medizin
Veröffentlichungsort: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-7189
Version: Published version
Publikationstyp: Zeitschriftenaufsatz
Nutzungsrechte: CC BY
Informationen zu den Nutzungsrechten: https://creativecommons.org/licenses/by/4.0/
Zeitschrift: Movement disorders
34
10
Seitenzahl oder Artikelnummer: 1536
1545
Verlag: Wiley
Verlagsort: New York, NY
Erscheinungsdatum: 2019
ISSN: 1531-8257
DOI der Originalveröffentlichung: 10.1002/mds.27808
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