Gabriel Gonzalez-Escamilla1, Muthuraman Muthuraman1, Martin M Reich2, Nabin Koirala1, Christian Riedel3, Martin Glaser4, Florian Lange2, Günther Deuschl5, Jens Volkmann2, Sergiu Groppa1. 1. Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany. 2. Department of Neurology, University Hospital Würzburg, Würzburg, Germany. 3. Department of Neuroradiology, UKSH, Christian-Albrechts-University Kiel, Kiel, Germany. 4. Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany. 5. Department of Neurology, UKSH, Christian-Albrechts-University Kiel, Kiel, Germany.
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.
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 dystoniapatients 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 dystoniapatients who benefit from DBS.
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