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      Vim-Thalamic Deep Brain Stimulation for Cervical Dystonia and Upper-Limb Tremor: Quantification by Markerless-3D Kinematics and Accelerometry

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          Abstract

          Background:

          Deep Brain Stimulation (DBS) for dystonia is usually targeted to the globus pallidus internus (GPi), though stimulation of the ventral-intermediate nucleus of the thalamus (Vim) can be an effective treatment for phasic components of dystonia including tremor. We report on a patient who developed a syndrome of bilateral upper limb postural and action tremor and progressive cervical dystonia with both phasic and tonic components which were responsive to Vim DBS. We characterize and quantify this effect using markerless-3D-kinematics combined with accelerometry.

          Methods:

          Stereo videography was used to record our subject in 3D. The DeepBehavior toolbox was applied to obtain timeseries of joint position for kinematic analysis [ 1]. Accelerometry was performed simultaneously for comparison with prior literature.

          Results:

          Bilateral Vim DBS improved both dystonic tremor magnitude and tonic posturing. DBS of the hemisphere contralateral to the direction of dystonic head rotation (left Vim) had greater efficacy. Assessment of tremor magnitude by 3D-kinematics was concordant with accelerometry and was able to quantify tonic dystonic posturing.

          Discussion:

          In this case, Vim DBS treated both cervical dystonic tremor and dystonic posturing. Markerless-3D-kinematics should be further studied as a method of quantifying and characterizing tremor and dystonia.

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          Most cited references37

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          Unified segmentation.

          A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians and is extended to incorporate a smooth intensity variation and nonlinear registration with tissue probability maps. A strategy for optimising the model parameters is described, along with the requisite partial derivatives of the objective function.
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            Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.

            One of the most challenging problems in modern neuroimaging is detailed characterization of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important component of this process. These spatiotemporal signals will aid in discriminating between related diseases, such as frontotemporal dementia (FTD) and Alzheimer's disease (AD), which manifest themselves in the same at-risk population. Here, we develop a novel symmetric image normalization method (SyN) for maximizing the cross-correlation within the space of diffeomorphic maps and provide the Euler-Lagrange equations necessary for this optimization. We then turn to a careful evaluation of our method. Our evaluation uses gold standard, human cortical segmentation to contrast SyN's performance with a related elastic method and with the standard ITK implementation of Thirion's Demons algorithm. The new method compares favorably with both approaches, in particular when the distance between the template brain and the target brain is large. We then report the correlation of volumes gained by algorithmic cortical labelings of FTD and control subjects with those gained by the manual rater. This comparison shows that, of the three methods tested, SyN's volume measurements are the most strongly correlated with volume measurements gained by expert labeling. This study indicates that SyN, with cross-correlation, is a reliable method for normalizing and making anatomical measurements in volumetric MRI of patients and at-risk elderly individuals.
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              Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations.

              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

                Contributors
                Journal
                Tremor Other Hyperkinet Mov (N Y)
                Tremor Other Hyperkinet Mov (N Y)
                2160-8288
                Tremor and Other Hyperkinetic Movements
                Ubiquity Press
                2160-8288
                10 March 2022
                2022
                : 12
                : 5
                Affiliations
                [1 ]Departments of Neurological Surgery and Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA, US
                [2 ]Department of Neurology, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, US
                [3 ]Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, US
                Author notes
                CORRESPONDING AUTHOR: Xenos L. Mason, MD Departments of Neurological Surgery and Neurology, Keck School of Medicine of USC (University of Southern California), 1520 San Pablo Street, Suite 3800, Los Angeles, CA 90033, US xenos.mason@ 123456med.usc.edu
                Author information
                https://orcid.org/0000-0002-5821-7275
                Article
                10.5334/tohm.673
                8916052
                35433109
                de9c6855-8c67-4553-8584-6cd9e1927911
                Copyright: © 2022 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 November 2021
                : 18 February 2022
                Funding
                Funded by: University of California, doi open-funder-registry10.13039/open_funder_registry10.13039/100005595;
                Funded by: U.S. Department of Veterans Affairs, doi open-funder-registry10.13039/open_funder_registry10.13039/100000738;
                This study was funded by the University of California, Los Angeles, and the U.S. Department of Veterans Affairs.
                Categories
                Brief Report

                deep brain stimulation,dystonia,tremor,accelerometry,kinematics,ventral thalamic nuclei

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