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Gonzalez-Escamilla G, Koirala N, Bange M, Glaser M, Pintea B, Dresel C, Deuschl G, Muthuraman M, Groppa S. Deciphering the Network Effects of Deep Brain Stimulation in Parkinson's Disease. Neurol Ther 2022; 11:265-282. [PMID: 35000133 PMCID: PMC8857357 DOI: 10.1007/s40120-021-00318-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/21/2021] [Indexed: 10/31/2022] Open
Abstract
INTRODUCTION Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an established therapy for Parkinson's disease (PD). However, a more detailed characterization of the targeted network and its grey matter (GM) terminals that drive the clinical outcome is needed. In this direction, the use of MRI after DBS surgery is now possible due to recent advances in hardware, opening a window for the clarification of the association between the affected tissue, including white matter fiber pathways and modulated GM regions, and the DBS-related clinical outcome. Therefore, we present a computational framework for reconstruction of targeted networks on postoperative MRI. METHODS We used a combination of preoperative whole-brain T1-weighted (T1w) and diffusion-weighted MRI data for morphometric integrity assessment and postoperative T1w MRI for electrode reconstruction and network reconstruction in 15 idiopathic PD patients. Within this framework, we made use of DBS lead artifact intensity profiles on postoperative MRI to determine DBS locations used as seeds for probabilistic tractography to cortical and subcortical targets within the motor circuitry. Lastly, we evaluated the relationship between brain microstructural characteristics of DBS-targeted brain network terminals and postoperative clinical outcomes. RESULTS The proposed framework showed robust performance for identifying the DBS electrode positions. Connectivity profiles between the primary motor cortex (M1), supplementary motor area (SMA), and DBS locations were strongly associated with the stimulation intensity needed for the optimal clinical outcome. Local diffusion properties of the modulated pathways were related to DBS outcomes. STN-DBS motor symptom improvement was highly associated with cortical thickness in the middle frontal and superior frontal cortices, but not with subcortical volumetry. CONCLUSION These data suggest that STN-DBS outcomes largely rely on the modulatory interference from cortical areas, particularly M1 and SMA, to DBS locations.
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Affiliation(s)
- Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany.
| | - Nabin Koirala
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, University Hospital Bergmannsheil, Bürkle de la Camp-Platz 1, 44789, Bochum, Germany
| | - Christian Dresel
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Günther Deuschl
- Department of Neurology, Schleswig-Holstein University Hospital UKSH, Arnold-Heller-Straße 3, 24105, Kiel, Germany
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany.
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Malaga KA, Costello JT, Chou KL, Patil PG. Atlas-independent, N-of-1 tissue activation modeling to map optimal regions of subthalamic deep brain stimulation for Parkinson disease. NEUROIMAGE-CLINICAL 2020; 29:102518. [PMID: 33333464 PMCID: PMC7736726 DOI: 10.1016/j.nicl.2020.102518] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/25/2020] [Accepted: 11/27/2020] [Indexed: 01/13/2023]
Abstract
Neuroanatomical variations among patients are obscured in atlas-based VTA modeling. N-of-1 neuroanatomical and VTA modeling enables patient-level precision. Mean optimal stimulation is dorsomedial to the STN, near its posterior half. Individual VTAs deviate from optimal stimulation sites to varying degrees. Optimal stimulation sites for rigidity, bradykinesia, and tremor partially overlap.
Background Motor outcomes after subthalamic deep brain stimulation (STN DBS) for Parkinson disease (PD) vary considerably among patients and strongly depend on stimulation location. The objective of this retrospective study was to map the regions of optimal STN DBS for PD using an atlas-independent, fully individualized (N-of-1) tissue activation modeling approach and to assess the relationship between patient-level therapeutic volumes of tissue activation (VTAs) and motor improvement. Methods The stimulation-induced electric field for 40 PD patients treated with bilateral STN DBS was modeled using finite element analysis. Neurostimulation models were generated for each patient, incorporating their individual STN anatomy, DBS lead position and orientation, anisotropic tissue conductivity, and clinical stimulation settings. A voxel-based analysis of the VTAs was then used to map the optimal location of stimulation. The amount of stimulation in specific regions relative to the STN was measured and compared between STNs with more and less optimal stimulation, as determined by their motor improvement scores and VTA. The relationship between VTA location and motor outcome was then assessed using correlation analysis. Patient variability in terms of STN anatomy, active contact position, and VTA location were also evaluated. Results from the N-of-1 model were compared to those from a simplified VTA model. Results Tissue activation modeling mapped the optimal location of stimulation to regions medial, posterior, and dorsal to the STN centroid. These regions extended beyond the STN boundary towards the caudal zona incerta (cZI). The location of the VTA and active contact position differed significantly between STNs with more and less optimal stimulation in the dorsal-ventral and anterior-posterior directions. Therapeutic stimulation spread noticeably more in the dorsal and posterior directions, providing additional evidence for cZI as an important DBS target. There were significant linear relationships between the amount of dorsal and posterior stimulation, as measured by the VTA, and motor improvement. These relationships were more robust than those between active contact position and motor improvement. There was high variability in STN anatomy, active contact position, and VTA location among patients. Spherical VTA modeling was unable to reproduce these results and tended to overestimate the size of the VTA. Conclusion Accurate characterization of the spread of stimulation is needed to optimize STN DBS for PD. High variability in neuroanatomy, stimulation location, and motor improvement among patients highlights the need for individualized modeling techniques. The atlas-independent, N-of-1 tissue activation modeling approach presented in this study can be used to develop and evaluate stimulation strategies to improve clinical outcomes on an individual basis.
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Affiliation(s)
- Karlo A Malaga
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Joseph T Costello
- Department of Electrical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Kelvin L Chou
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA; Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA
| | - Parag G Patil
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Department of Neurology, University of Michigan, Ann Arbor, MI, USA; Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA.
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Prent N, Potters WV, Boon LI, Caan MWA, de Bie RMA, van den Munckhof P, Schuurman PR, van Rootselaar AF. Distance to white matter tracts is associated with deep brain stimulation motor outcome in Parkinson's disease. J Neurosurg 2020; 133:433-442. [PMID: 31349226 DOI: 10.3171/2019.5.jns1952] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 05/01/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) of the subthalamic nucleus (STN) alleviates motor symptoms in patients with Parkinson's disease (PD). However, the underlying mechanism of tremor suppression is not well understood. Stimulation of white matter tracts, such as the dentatorubrothalamic tract (DRT), might be involved. Also, side effects, including dysarthria, might result from (unwanted) stimulation of white matter tracts in proximity to the STN. The aim of this study was to establish an association between stimulation effect on tremor and dysarthria and stimulation location relative to relevant white matter tracts. METHODS In 35 PD patients in whom a bilateral STN DBS system was implanted, the authors established clinical outcome measures per electrode contact. The distance from each stimulation location to the center of the DRT, corticopontocerebellar tract, pyramidal tract (PT), and medial lemniscus was determined using diffusion-weighted MRI data. Clinical outcome measures were subsequently related to the distances to the white matter tracts. RESULTS Patients with activated contacts closer to the DRT showed increased tremor improvement. Proximity of activated contacts to the PT was associated with dysarthria. CONCLUSIONS Proximity to specific white matter tracts is associated with tremor outcome and side effects in DBS. This knowledge can help to optimize both electrode placement and postsurgical electrode contact selection. Presurgical white matter tract visualization may improve targeting and DBS outcome. These findings are of interest not only for treatment in PD, but potentially also for other (movement) disorders.
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Affiliation(s)
- Naomi Prent
- 1Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience
| | - Wouter V Potters
- 1Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience
| | - Lennard I Boon
- 1Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience
- 2Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience
| | - Matthan W A Caan
- 3Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience
| | - Rob M A de Bie
- 5Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Pepijn van den Munckhof
- 4Department of Neurosurgery, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience; and
| | - P Richard Schuurman
- 4Department of Neurosurgery, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience; and
| | - Anne-Fleur van Rootselaar
- 1Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience
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Juttukonda MR, Franco G, Englot DJ, Lin YC, Petersen KJ, Trujillo P, Hedera P, Landman BA, Kang H, Donahue MJ, Konrad PE, Dawant BM, Claassen DO. White matter differences between essential tremor and Parkinson disease. Neurology 2018; 92:e30-e39. [PMID: 30504432 DOI: 10.1212/wnl.0000000000006694] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 09/05/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess white matter integrity in patients with essential tremor (ET) and Parkinson disease (PD) with moderate to severe motor impairment. METHODS Sedated participants with ET (n = 57) or PD (n = 99) underwent diffusion tensor imaging (DTI) and fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity values were computed. White matter tracts were defined using 3 well-described atlases. To determine candidate white matter regions that differ between ET and PD groups, a bootstrapping analysis was applied using the least absolute shrinkage and selection operator. Linear regression was applied to assess magnitude and direction of differences in DTI metrics between ET and PD populations in the candidate regions. RESULTS Fractional anisotropy values that differentiate ET from PD localize primarily to thalamic and visual-related pathways, while diffusivity differences localized to the cerebellar peduncles. Patients with ET exhibited lower fractional anisotropy values than patients with PD in the lateral geniculate body (p < 0.01), sagittal stratum (p = 0.01), forceps major (p = 0.02), pontine crossing tract (p = 0.03), and retrolenticular internal capsule (p = 0.04). Patients with ET exhibited greater radial diffusivity values than patients with PD in the superior cerebellar peduncle (p < 0.01), middle cerebellar peduncle (p = 0.05), and inferior cerebellar peduncle (p = 0.05). CONCLUSIONS Regionally, distinctive white matter microstructural values in patients with ET localize to the cerebellar peduncles and thalamo-cortical visual pathways. These findings complement recent functional imaging studies in ET but also extend our understanding of putative physiologic features that account for distinctions between ET and PD.
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Affiliation(s)
- Meher R Juttukonda
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Giulia Franco
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Dario J Englot
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Ya-Chen Lin
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Kalen J Petersen
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Paula Trujillo
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Peter Hedera
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Bennett A Landman
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Hakmook Kang
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Manus J Donahue
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Peter E Konrad
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Benoit M Dawant
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN
| | - Daniel O Claassen
- From the Departments of Radiology and Radiological Sciences (M.R.J., M.J.D.), Neurological Surgery (D.J.E., P.E.K.), Biostatistics (Y.-C.L., H.K.), Neurology (P.T., P.H., M.J.D.), and Psychiatry (M.J.D.), Vanderbilt University Medical Center, Nashville, TN; Department of Pathophysiology and Transplantation (G.F.) University of Milan, Italy; and Chemical and Physical Biology Program (K.J.P.) and Departments of Electrical Engineering (B.A.L., B.M.D.), Computer Engineering (B.A.L., B.M.D.), Computer Science and Biomedical Engineering (B.A.L., B.M.D.), and Neurology (D.O.C.), Vanderbilt University, Nashville, TN.
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Rodrigues NB, Mithani K, Meng Y, Lipsman N, Hamani C. The Emerging Role of Tractography in Deep Brain Stimulation: Basic Principles and Current Applications. Brain Sci 2018; 8:brainsci8020023. [PMID: 29382119 PMCID: PMC5836042 DOI: 10.3390/brainsci8020023] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Revised: 01/24/2018] [Accepted: 01/26/2018] [Indexed: 12/30/2022] Open
Abstract
Diffusion tensor imaging (DTI) is an MRI-based technique that delineates white matter tracts in the brain by tracking the diffusion of water in neural tissue. This methodology, known as “tractography”, has been extensively applied in clinical neuroscience to explore nervous system architecture and diseases. More recently, tractography has been used to assist with neurosurgical targeting in functional neurosurgery. This review provides an overview of DTI principles, and discusses current applications of tractography for improving and helping develop novel deep brain stimulation (DBS) targets.
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Affiliation(s)
- Nelson B Rodrigues
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada.
| | - Karim Mithani
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
| | - Ying Meng
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada.
| | - Nir Lipsman
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada.
| | - Clement Hamani
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada.
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