RT Journal Article
SR Electronic
T1 Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 322008
DO 10.1101/322008
A1 Andreas Horn
A1 Ningfei Li
A1 Till A Dembek
A1 Ari Kappel
A1 Chadwick Boulay
A1 Siobhan Ewert
A1 Anna Tietze
A1 Andreas Husch
A1 Thushara Perera
A1 Wolf-Julian Neumann
A1 Marco Reisert
A1 Hang Si
A1 Robert Oostenveld
A1 Christopher Rorden
A1 Fang-Cheng Yeh
A1 Qianqian Fang
A1 Todd M Herrington
A1 Johannes Vorwerk
A1 Andrea A. Kühn
YR 2018
UL http://biorxiv.org/content/early/2018/08/28/322008.abstract
AB 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.List of abbreviationsANTsAdvanced Normalization Tools, see http://stnava.github.io/ANTs/BSpline-SyNANTs normalization method; Explicit B-spline regularization in symmetric diffeomorphic image registrationCOREAlgorithm for “reconstruction of electrode contact positions” defined in Horn & Kühn 2014DARTELSPM normalization method; A fast diffeomorphic image registration algorithm.DiODeDirectional Orientation Detection (Sitz et al. 2017)dMRIDiffusion-weighted MRI – in the context of diffusion-imaging based tractography.FAFractional AnisotropyFGATIRFast Grey Matter Acquisition T1 Inversion RecoveryFLIRTFMRIB’s Linear Image Registration ToolFNIRTFSL normalization method; FMRIB’s Nonlinear Image Registration ToolFSLFMRIB Software Library, see https://fsl.fmrib.ox.ac.uk/GNURecursive acronym for “GNU’s Not Unix.”; GNU GPL is a popular open license supported by the Free Software Foundation (see http://www.gnu.org). The Free Software Foundation (FSF) is a nonprofit with a worldwide mission to promote computer user freedom.Gpiinternal segment of the globus pallidusGpeexternal segment of the globus pallidusGQIGeneralized q-sampling imaging, dMRI processing method implemented in DSI studioHCPHuman Connectome ProjectLEDDLevodopa Equivalent Daily DosageMAGeT BrainMultiple Automatically Generated Templates brain segmentation algorithm, see https://github.com/CobraLab/MAGeTbrainPaCERPrecise and Convenient Electrode Reconstruction for DBS, see https://adhusch.github.io/PaCER/PCAPrincipal Component AnalysisPPMIParkinson‘s Disease Progression Marker InitiativePPNPedunculopontine nucleusRNred nucleusROIRegion of InterestRSMERoot-mean-square errorQSMQuantitative Susceptibility Mappingrs-fMRIResting-state functional MRISHOOTSPM normalization method; Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisationSPMStatistic Parametric Mapping, see http://www.fil.ion.ucl.ac.uk/spm/software/spm12/STNsubthalamic nucleusSyNANTs normalization method; Symmetric diffeomorphic image registration / symmetric image normalizationTRACAlgorithm for “trajectory reconstruction” defined in Horn & Kühn 2014UPDRSUnified Parkinson‘s Disease Rating ScaleVTAVolume of Tissue Activated