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contributor authorDai, Wei
contributor authorAstary, Garrett W.
contributor authorKasinadhuni, Aditya K.
contributor authorCarney, Paul R.
contributor authorMareci, Thomas H.
contributor authorSarntinoranont, Malisa
date accessioned2017-05-09T01:26:06Z
date available2017-05-09T01:26:06Z
date issued2016
identifier issn0148-0731
identifier otherbio_138_05_051007.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/160381
description abstractConvection enhanced delivery (CED) is a promising novel technology to treat neural diseases, as it can transport macromolecular therapeutic agents greater distances through tissue by direct infusion. To minimize offtarget delivery, our group has developed 3D computational transport models to predict infusion flow fields and tracer distributions based on magnetic resonance (MR) diffusion tensor imaging data sets. To improve the accuracy of our voxelized models, generalized anisotropy (GA), a scalar measure of a higher order diffusion tensor obtained from high angular resolution diffusion imaging (HARDI) was used to improve tissue segmentation within complex tissue regions of the hippocampus by capturing small feature fissures. Simulations were conducted to reveal the effect of these fissures and cerebrospinal fluid (CSF) boundaries on CED tracer diversion and mistargeting. Sensitivity analysis was also conducted to determine the effect of dorsal and ventral hippocampal infusion sites and tissue transport properties on drug delivery. Predicted CED tissue concentrations from this model are then compared with experimentally measured MR concentration profiles. This allowed for more quantitative comparison between model predictions and MR measurement. Simulations were able to capture infusate diversion into fissures and other CSF spaces which is a major source of CED mistargeting. Such knowledge is important for proper surgical planning.
publisherThe American Society of Mechanical Engineers (ASME)
titleVoxelized Model of Brain Infusion That Accounts for Small Feature Fissures: Comparison With Magnetic Resonance Tracer Studies
typeJournal Paper
journal volume138
journal issue5
journal titleJournal of Biomechanical Engineering
identifier doi10.1115/1.4032626
journal fristpage51007
journal lastpage51007
identifier eissn1528-8951
treeJournal of Biomechanical Engineering:;2016:;volume( 138 ):;issue: 005
contenttypeFulltext


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