Patient-Specific Anisotropic Volume of Tissue Activated with the Lead-DBS Toolbox.

Garza, Roberto; Segura Amil, Alba; Nowacki, Andreas; Pollo, Claudio; Nguyen, T. A. Khoa (2021). Patient-Specific Anisotropic Volume of Tissue Activated with the Lead-DBS Toolbox. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2021, pp. 6285-6288. IEEE 10.1109/EMBC46164.2021.9629810

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Deep brain stimulation is an effective neurosurgical intervention for movement disorders such as Parkinson's disease. Despite its success, the underlying mechanisms are still debated. One tool to better understand them is the Volume of Tissue Activated (VTA), that estimates the region activated by electrical stimulation. Different estimation approaches exist, these typically assume isotropic tissue properties and modelling of anisotropy is often lacking.The present work was aimed at developing and testing a method for patient-specific VTA estimation that incorporated an anisotropic conduction model. Our method was implemented within the open-source toolbox Lead-DBS and is accessible to the public.The present method was further tested with two patient cases and compared to a standard Lead-DBS pipeline for VTA estimation. This showed encouraging similarities in one test scenario and expected differences in another test scenario. Further validation with a wider cohort is warranted.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research

UniBE Contributor:

Garza, Roberto; Segura Amil, Alba; Nowacki, Andreas; Pollo, Claudio and Nguyen, Thuy Anh Khoa

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

2694-0604

Publisher:

IEEE

Language:

English

Submitter:

Nicole Söll

Date Deposited:

13 Jan 2022 15:02

Last Modified:

13 Jan 2022 15:11

Publisher DOI:

10.1109/EMBC46164.2021.9629810

PubMed ID:

34892550

BORIS DOI:

10.48350/162717

URI:

https://boris.unibe.ch/id/eprint/162717

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