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White matter tracing combined with electric field simulation –€“ A patient-specific approach for deep brain stimulation
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
Laboratory of Mathematics in Imaging, Brigham and Women's Hospital, Harvard Medical School, USA / Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, USA.
Laboratory of Mathematics in Imaging, Brigham and Women's Hospital, Harvard Medical School, USA.
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2019 (English)In: NeuroImage: Clinical, ISSN 0353-8842, E-ISSN 2213-1582, Vol. 24, p. 1-11, article id 102026Article in journal (Refereed) Published
Abstract [en]

Objective

Deep brain stimulation (DBS) in zona incerta (Zi) is used for symptom alleviation in essential tremor (ET). Zi is positioned along the dentato-rubro-thalamic tract (DRT). Electric field simulations with the finite element method (FEM) can be used for estimation of a volume where the stimulation affects the tissue by applying a fixed isolevel (VDBS). This work aims to develop a workflow for combined patient-specific electric field simulation and white matter tracing of the DRT, and to investigate the influence on the VDBS from different brain tissue models, lead design and stimulation modes. The novelty of this work lies in the combination of all these components.

Method

Patients with ET were implanted in Zi (lead 3389, n = 3, voltage mode; directional lead 6172, n = 1, current mode). Probabilistic reconstruction from diffusion MRI (dMRI) of the DRT (n = 8) was computed with FSL Toolbox. Brain tissue models were created for each patient (two homogenous, one heterogenous isotropic, one heterogenous anisotropic) and the respective VDBS (n = 48) calculated from the Comsol Multiphysics FEM simulations. The DRT and VDBS were visualized with 3DSlicer and superimposed on the preoperative T2 MRI, and the common volumes calculated. Dice Coefficient (DC) and level of anisotropy were used to evaluate and compare the brain models.

Result

Combined patient-specific tractography and electric field simulation was designed and evaluated, and all patients showed benefit from DBS. All VDBS overlapped the reconstructed DRT. Current stimulation showed prominent difference between the tissue models, where the homogenous grey matter deviated most (67 < DC < 69). Result from heterogenous isotropic and anisotropic models were similar (DC > 0.95), however the anisotropic model consistently generated larger volumes related to a greater extension of the electric field along the DBS lead. Independent of tissue model, the steering effect of the directional lead was evident and consistent.

Conclusion

A workflow for patient-specific electric field simulations in combination with reconstruction of DRT was successfully implemented. Accurate tissue classification is essential for electric field simulations, especially when using the current control stimulation. With an accurate targeting and tractography reconstruction, directional leads have the potential to tailor the electric field into the desired region.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 24, p. 1-11, article id 102026
Keywords [en]
Deep brain stimulation (DBS), Essential tremor (ET), Diffusion MRI (dMRI), Tractography, Dentato-rubro-thalamic tract (DRT), Zona Incerta (Zi), Electrical conductivity tensor
National Category
Medical Laboratory and Measurements Technologies Medical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-162461DOI: 10.1016/j.nicl.2019.102026ISI: 000504663800147OAI: oai:DiVA.org:liu-162461DiVA, id: diva2:1375538
Note

Funding agencies:  Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [SSF BD150032]; Swedish Research CouncilSwedish Research Council [VR 2016-03564]; National Institute of HealthUnited States Department of Health & Human ServicesNational In

Available from: 2019-12-05 Created: 2019-12-05 Last updated: 2020-01-09Bibliographically approved

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Nordin, TeresaZsigmond, PeterWårdell, Karin
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