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Patient-Specific Brain Modelling for Deep Brain Stimulation Simulations
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Center for Medical Image Science and Visualization (CMIV). (MINT)ORCID iD: 0000-0002-0012-7867
University College London, UK.
University College London, UK.
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
2013 (English)In: Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, IEEE , 2013, 148-151 p.Conference paper, Published paper (Refereed)
Abstract [en]

A patient-specific modelling technique for simulation of the electric field surrounding deep brain stimulation (DBS) electrodes has been adapted to Ti and T2-weigthed, proton density (PrD) and spoiled gradient echo (SPGR) magnetic resonance imaging (MRI) sequences. Electrical conductivity (a) assignment of gray and white matter was made dependent on the neuromodulator settings. Nine brain models with different a were created. Four PrD/SPGR images tuned differently were fused. Five models based on the same T2 batch of MRI were set up with different sigma. Finite element simulations (2, 3, 4, 5 V) of bilateral DBS electrodes positioned in the globus pallidus internus (GPi) were created. The electric field volumes were calculated for isosurfaces of 0.2V/mm and 0.1V/mm. A reference T2-model was used for comparison. At 0.1V/mm white matter had a larger influence when set to ten times the original value. Homogenous models responded similar. It was found that the method was sensitive to very small electrical conductivity variations and consequently to the corresponding anatomical variations in tissue type.

Place, publisher, year, edition, pages
IEEE , 2013. 148-151 p.
Series
International IEEE EMBS Conference on Neural Engineering, ISSN 1948-3546
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-105594DOI: 10.1109/NER.2013.6695893ISI: 000331259200038ISBN: 9781467319690 (electronic)ISBN: 9781467319676 (print)ISBN: 9781467319683 (electronic)OAI: oai:DiVA.org:liu-105594DiVA: diva2:708696
Conference
6th International IEEE EMBS Conference on Neural Engineering (NER)
Available from: 2014-03-28 Created: 2014-03-27 Last updated: 2017-02-14Bibliographically approved

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Wårdell, KarinAndersson, Mats

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