SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

An internationally recognized leader in visualization, scientific computing, and image analysis

SCI Publications

2010


A. Chaturvedi, C.R. Butson, S.F. Lempka, S.E. Cooper, C.C. McIntyre. “Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions,” In Brain Stimulation, Vol. 3, No. 2, Elsevier Inc., pp. 65--67. April, 2010.
ISSN: 1935-861X
DOI: 10.1016/j.brs.2010.01.003
PubMed ID: 20607090

ABSTRACT

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Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become the surgical therapy of choice for medically intractable Parkinson's disease. However, quantitative understanding of the interaction between the electric field generated by DBS and the underlying neural tissue is limited. Recently, computational models of varying levels of complexity have been used to study the neural response to DBS. The goal of this study was to evaluate the quantitative impact of incrementally incorporating increasing levels of complexity into computer models of STN DBS. Our analysis focused on the direct activation of experimentally measureable fiber pathways within the internal capsule (IC). Our model system was customized to an STN DBS patient and stimulation thresholds for activation of IC axons were calculated with electric field models that ranged from an electrostatic, homogenous, isotropic model to one that explicitly incorporated the voltage-drop and capacitance of the electrode-electrolyte interface, tissue encapsulation of the electrode, and diffusion-tensor based 3D tissue anisotropy and inhomogeneity. The model predictions were compared to experimental IC activation defined from electromyographic (EMG) recordings from eight different muscle groups in the contralateral arm and leg of the STN DBS patient. Coupled evaluation of the model and experimental data showed that the most realistic predictions of axonal thresholds were achieved with the most detailed model. Furthermore, the more simplistic neurostimulation models substantially overestimated the spatial extent of neural activation.

Keywords: Action Potentials, Action Potentials: physiology, Computer Simulation, Deep Brain Stimulation, Deep Brain Stimulation: instrumentation, Deep Brain Stimulation: methods, Humans, Male, Middle Aged, Models, Neurological, Parkinson Disease, Parkinson Disease: therapy, Subthalamic Nucleus, Subthalamic Nucleus: physiology


A.N.M. Imroz Choudhury, M.D. Steffen, J.E. Guilkey, S.G. Parker. “Enhanced Understanding of Particle Simulations Through Deformation-Based Visualization,” In Computer Modeling in Engineering & Sciences, Vol. 63, No. 2, pp. 117--136. 2010.


J. Cui, P. Rosen, V. Popescu, C. Hoffmann. “A Curved Ray Camera for Handling Occlusions through Continuous Multiperspective Visualization,” In IEEE Transactions on Visualization and Computer Graphics (Visualization 2010), pp. 1235--1242. November/December, 2010.


E.B. Dam, P.T. Fletcher, S.M. Pizer. “Automatic shape model building based on principal geodesic analysis bootstrapping,” In Medical Image Analysis, Vol. 12, No. 2, Note: Epub Feb 2 2010, pp. 136--151. 2010.
PubMed ID: 18178124


J. Daniels, E.W. Anderson, L.G. Nonato, C.T. Silva. “Interactive Vector Field Feature Identification,” In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2010 IEEE Visualization Conference, Vol. 16, No. 6, pp. 1560--1568. 2010.
DOI: 10.1109/TVCG.2010.170
PubMed ID: 20975198


B.C. Davis, P.T. Fletcher, E. Bullitt, S. Joshi. “Population Shape Regression from Random Design Data,” In International Journal of Computer Vision, Vol. 90, No. 1, Note: Marr Prize Special Issue, pp. 255--266. October, 2010.
DOI: 10.1109/ICCV.2007.4408977


N.J. Drury, B.J. Ellis, J.A. Weiss, P.J. McMahon, R.E. Debski. “The impact of glenoid labrum thickness and modulus on labrum and glenohumeral capsule function,” In Journal of Biomechanical Engineering, Vol. 132, No. 12, Note: Awarded 2010 Skalak Best Paper!, pp. 121003--121010. 2010.
DOI: 10.1115/1.4002622


S. Durrleman, X. Pennec, A. Trouvé, N. Ayache, J. Braga. “Comparison of the endocast growth of chimpanzees and bonobos via temporal regression and spatiotemporal registration,” In Proceedings of the MICCAI Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data, Beijing, China, pp. (in press). September, 2010.


S. Durrleman, P. Fillard, X. Pennec, A. Trouvé, N. Ayache. “Registration, Atlas Estimation and Variability Analysis of White Matter Fiber Bundles Modeled as Currents,” In NeuroImage, Vol. 55, No. 3, pp. 1073--1090. 2010.
DOI: 10.1016/j.neuroimage.2010.11.056


M. El-Sayed, R.G. Steen, M.D. Poe, T.C. Bethea, G. Gerig, J. Lieberman, L. Sikich. “Deficits in gray matter volume in psychotic youth with schizophrenia-spectrum disorders are not evident in psychotic youth with mood disorders,” In J Psychiatry Neurosci, July, 2010.


M. El-Sayed, R.G. Steen, M.D. Poe, T.C. Bethea, G. Gerig, J. Lieberman, L. Sikich. “Brain volumes in psychotic youth with schizophrenia and mood disorders,” In Journal of Psychiatry and Neuroscience, Vol. 35, No. 4, pp. 229--236. July, 2010.
PubMed ID: 20569649


T. Etiene, L.G. Nonato, C.E. Scheidegger, J. Tierny, T.J. Peters, V. Pascucci, R.M. Kirby, C.T. Silva. “Topology Verification for Isosurface Extraction,” SCI Technical Report, No. UUSCI-2010-003, SCI Institute, University of Utah, 2010.


P.T. Fletcher, R.T. Whitaker, R. Tao, M.B. DuBray, A. Froehlich, C. Ravichandran, A.L. Alexander, E.D. Bigler, N. Lange, J.E. Lainhart. “Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism,” In NeuroImage, Vol. 51, No. 3, Note: Epub Feb 2 2010, pp. 1117--1125. July, 2010.
PubMed ID: 20132894


T. Fogal, J. Krüger. “Tuvok, an Architecture for Large Scale Volume Rendering,” In Proceedings of the 15th International Workshop on Vision, Modeling, and Visualization, pp. 139--146. November, 2010.
DOI: 10.2312/PE/VMV/VMV10/139-146


T. Fogal, H. Childs, S. Shankar, J. Krüger, R.D. Bergeron, P. Hatcher. “Large Data Visualization on Distributed Memory Multi-GPU Clusters,” In Proceedings of High Performance Graphics 2010, pp. 57--66. 2010.


S.E. Geneser, J.D. Hinkle, R.M. Kirby, Brian Wang, B. Salter, S. Joshi. “Quantifying Variability in Radiation Dose Due to Respiratory-Induced Tumor Motion,” In Medical Image Analysis, Vol. 15, No. 4, pp. 640--649. 2010.
DOI: 10.1016/j.media.2010.07.003


S. Gerber, T. Tasdizen, P.T. Fletcher, S. Joshi, R.T. Whitaker, the Alzheimers Disease Neuroimaging Initiative (ADNI). “Manifold modeling for brain population analysis,” In Medical Image Analysis, Special Issue on the 12th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009, Vol. 14, No. 5, Note: Awarded MICCAI 2010, Best of the Journal Issue Award, pp. 643--653. 2010.
ISSN: 1361-8415
DOI: 10.1016/j.media.2010.05.008
PubMed ID: 20579930


S. Gerber, P.-T. Bremer, V. Pascucci, R.T. Whitaker. “Visual Exploration of High Dimensional Scalar Functions,” In IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics, Vol. 16, No. 6, IEEE, pp. 1271--1280. Nov, 2010.
DOI: 10.1109/TVCG.2010.213
PubMed ID: 20975167
PubMed Central ID: PMC3099238


J.H. Gilmore, C. Kang, D.D. Evans, H.M. Wolfe, M.D. Smith, J.A. Lieberman, W. Lin, R.M. Hamer, M. Styner, G. Gerig. “Prenatal and Neonatal Brain Structure and White Matter Maturation in Children at High Risk for Schizophrenia,” In American Journal of Psychiatry, Vol. 167, No. 9, Note: Epub 2010 Jun 1, pp. 1083--1091. September, 2010.
PubMed ID: 20516153


J.H. Gilmore, J.E. Schmitt, R.C. Knickmeyer, J.K. Smith, W. Lin, M. Styner, G. Gerig, M.C. Neale. “Genetic and environmental contributions to neonatal brain structure: A twin study,” In Human Brain Mapping, Vol. 31, No. 8, Note: ePub 8 Jan 2010, pp. 1174--1182. 2010.
PubMed ID: 20063301