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      Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor

      Author(s): 1 , 1 , 1 , 1 , 1 , 2 , 1 , 3
      Publication date Created:
      Publication date (Electronic):
      Journal: Brain
      Publisher: Oxford University Press (OUP)

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          Abstract

          Al-Fatly et al. establish predictive connectivity maps of deep brain stimulation in essential tremor. They demonstrate that electrode connectivity to tremor-associated brain areas can predict postoperative improvement and that these maps can be somatotopically segregated according to the tremor-affected body parts.

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          Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

          Andreas Horn, Martin Reich, Johannes Vorwerk … (2017)
          The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.
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            Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

            Andreas Horn, Ningfei Li, Till A. Dembek … (2019)
            Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural / functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient’s preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.
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              Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations.

              Andreas Horn, Andrea Kühn (2015)
              To determine placement of electrodes after deep brain stimulation (DBS) surgery, a novel toolbox that facilitates both reconstruction of the lead electrode trajectory and the contact placement is introduced. Using the toolbox, electrode placement can be reconstructed and visualized based on the electrode-induced artifacts on post-operative magnetic resonance (MR) or computed tomography (CT) images. Correct electrode placement is essential for efficacious treatment with DBS. Post-operative knowledge about the placement of DBS electrode contacts and trajectories is a promising tool for clinical evaluation of DBS effects and adverse effects. It may help clinicians in identifying the best stimulation contacts based on anatomical target areas and may even shorten test stimulation protocols in the future. Fifty patients that underwent DBS surgery were analyzed in this study. After normalizing the post-operative MR/CT volumes into standard Montreal Neurological Institute (MNI)-stereotactic space, electrode leads (n=104) were detected by a novel algorithm that iteratively thresholds each axial slice and isolates the centroids of the electrode artifacts within the MR/CT-images (MR only n=32, CT only n=10, MR and CT n=8). Two patients received four, the others received two quadripolar DBS leads bilaterally, summing up to a total of 120 lead localizations. In a second reconstruction step, electrode contacts along the lead trajectories were reconstructed by using templates of electrode tips that had been manually created beforehand. Reconstructions that were made by the algorithm were finally compared to manual surveys of contact localizations. The algorithm was able to robustly accomplish lead reconstructions in an automated manner in 98% of electrodes and contact reconstructions in 69% of electrodes. Using additional subsequent manual refinement of the reconstructed contact positions, 118 of 120 electrode lead and contact reconstructions could be localized using the toolbox. Taken together, the toolbox presented here allows for a precise and fast reconstruction of DBS contacts by proposing a semi-automated procedure. Reconstruction results can be directly exported to two- and three-dimensional views that show the relationship between DBS contacts and anatomical target regions. The toolbox is made available to the public in form of an open-source MATLAB repository.
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                Author and article information

                Journal
                Title: Brain
                Publisher: Oxford University Press (OUP)
                ISSN (Print): 0006-8950
                ISSN (Electronic): 1460-2156
                Publication date Created: October 2019
                Publication date Created: October 01 2019
                Publication date Created: August 03 2019
                Publication date Other: October 2019
                Publication date (Print): October 01 2019
                Publication date (Electronic): August 03 2019
                Volume: 142
                Issue: 10
                Pages: 3086-3098
                Affiliations
                [1 ]Department of Neurology with Experimental Neurology, Movement Disorders and Neuromodulation Unit, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
                [2 ]Berlin Institute of Health, Berlin, Germany
                [3 ]Exzellenzcluster NeuroCure, Charité – Universitätsmedizin Berlin, Berlin, Germany
                Article
                DOI: 10.1093/brain/awz236
                PubMed ID: 31377766
                SO-VID: 0cb885cd-8960-4491-8baf-18f86bf0286c
                Copyright © © 2019
                License:

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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