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A diffusion tensor-based finite element model of microdialysis in the deep brain
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). (MINT)ORCID iD: 0000-0002-0012-7867
2015 (English)In: Computer Methods in Biomechanics and Biomedical Engineering, ISSN 1025-5842, E-ISSN 1476-8259, Vol. 18, no 2, 201-212 p.Article in journal (Refereed) Published
Abstract [en]

Microdialysis of the basal ganglia was recently used to study neurotransmitter levels in relation to deep brain stimulation. In order to estimate the anatomical origin of the obtained data, the maximum tissue volume of influence (TVImax) for a microdialysis catheter was simulated using the finite element method. This study investigates the impact of brain heterogeneity and anisotropy on the TVImax using diffusion tensor imaging (DTI) to create a second-order tensor model of the basal ganglia. Descriptive statistics showed that the maximum migration distance for neurotransmitters varied by up to 55% (n = 98,444) for DTI-based simulations compared with an isotropic reference model, and the anisotropy differed between different targets in accordance with theory. The size of the TVImax was relevant in relation to the size of the anatomical structures of interest, and local tissue properties should be accounted for when relating microdialysis data to their anatomical targets.

Place, publisher, year, edition, pages
Taylor & Francis, 2015. Vol. 18, no 2, 201-212 p.
National Category
Other Medical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-91886DOI: 10.1080/10255842.2013.789103ISI: 000343606800011PubMedID: 23627319OAI: oai:DiVA.org:liu-91886DiVA: diva2:619465
Available from: 2013-05-03 Created: 2013-05-03 Last updated: 2017-12-06Bibliographically approved

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Diczfalusy, ElinAndersson, MatsWårdell, Karin

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