A Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment|
B.M. Burton, J.D. Tate, B. Erem, D.J. Swenson, D.F. Wang, D.H. Brooks, P.M. van Dam, R.S. MacLeod. In Proceedings of the 2011 IEEE Int. Conf. Engineering and Biology Society (EMBC), pp. 267--270. 2011.
PubMed ID: 22254301
PubMed Central ID: PMC3337752
Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems.
Morse Set Classification and Hierarchical Refinement using Conley Index|
Guoning Chen, Qingqing Deng, Andrzej Szymczak, Robert S. Laramee, and Eugene Zhang. In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. 18, No. 5, pp. 767--782. June, 2011.
PubMed ID: 21690641
Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion. Our framework allows a Morse set to be refined through a local update of the flow combinatorialization graph, as well as the connection regions between Morse sets. The computation is fast because the most expensive computation is concentrated on a small portion of the domain. Furthermore, the present work allows the generation of a topologically consistent hierarchy of MCGs, which cannot be obtained using a global method. The classification of the extracted Morse sets is a crucial step for the construction of the MCG, for which the Poincaré index is inadequate. We make use of an upper bound for the Conley index, provided by the Betti numbers of an index pair for a translation along the flow, to classify the Morse sets. This upper bound is sufficiently accurate for Morse set classification and provides supportive information for the automatic refinement process. An improved visualization technique for MCG is developed to incorporate the Conley indices. Finally, we apply the proposed techniques to a number of synthetic and real-world simulation data to demonstrate their utility.
|A wildland fire modeling and visualization environment,
J. Mandel, J.D. Beezley, A. Kochanski, V.Y. Kondratenko, L. Zhang, E. Anderson, J. Daniels II, C.T. Silva, C.R. Johnson. In Proceedings of the Ninth Symposium on Fire and Forest Meteorology, pp. (published online). 2011.
Cardiac Position Sensitivity Study in the Electrocardiographic Forward Problem Using Stochastic Collocation and Boundary Element Methods|
D.J. Swenson, S.E. Geneser, J.G. Stinstra, R.M. Kirby, R.S. MacLeod. In Annals of Biomedical Engineering, Vol. 39, No. 12, pp. 2900--2910. 2011.
PubMed ID: 21909818
PubMed Central ID: PMC336204
The electrocardiogram (ECG) is ubiquitously employed as a diagnostic and monitoring tool for patients experiencing cardiac distress and/or disease. It is widely known that changes in heart position resulting from, for example, posture of the patient (sitting, standing, lying) and respiration significantly affect the body-surface potentials; however, few studies have quantitatively and systematically evaluated the effects of heart displacement on the ECG. The goal of this study was to evaluate the impact of positional changes of the heart on the ECG in the specific clinical setting of myocardial ischemia. To carry out the necessary comprehensive sensitivity analysis, we applied a relatively novel and highly efficient statistical approach, the generalized polynomial chaos-stochastic collocation method, to a boundary element formulation of the electrocardiographic forward problem, and we drove these simulations with measured epicardial potentials from whole-heart experiments. Results of the analysis identified regions on the body-surface where the potentials were especially sensitive to realistic heart motion. The standard deviation (STD) of ST-segment voltage changes caused by the apex of a normal heart, swinging forward and backward or side-to-side was approximately 0.2 mV. Variations were even larger, 0.3 mV, for a heart exhibiting elevated ischemic potentials. These variations could be large enough to mask or to mimic signs of ischemia in the ECG. Our results suggest possible modifications to ECG protocols that could reduce the diagnostic error related to postural changes in patients possibly suffering from myocardial ischemia.
Analysis of Large-Scale Scalar Data Using Hixels|
D. Thompson, J.A. Levine, J.C. Bennett, P.-T. Bremer, A. Gyulassy, V. Pascucci, P.P. Pebay. In Proceedings of the 2011 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), Providence, RI, pp. 23--30. 2011.
Scalable Parallel Building Blocks for Custom Data Analysis|
T. Peterka, R. Ross, A. Gyulassy, V. Pascucci, W. Kendall, H.-W. Shen, T.-Y. Lee, A. Chaudhuri. In Proceedings of the 2011 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), pp. 105--112. October, 2011.
We present a set of building blocks that provide scalable data movement capability to computational scientists and visualization researchers for writing their own parallel analysis. The set includes scalable tools for domain decomposition, process assignment, parallel I/O, global reduction, and local neighborhood communicationtasks that are common across many analysis applications. The global reduction is performed with a new algorithm, described in this paper, that efficiently merges blocks of analysis results into a smaller number of larger blocks. The merging is configurable in the number of blocks that are reduced in each round, the number of rounds, and the total number of resulting blocks. We highlight the use of our library in two analysis applications: parallel streamline generation and parallel Morse-Smale topological analysis. The first case uses an existing local neighborhood communication algorithm, whereas the latter uses the new merge algorithm.
Adaptive Extraction and Quantification of Geophysical Vortices|
S. Williams, M. Petersen, P.-T. Bremer, M. Hecht, V. Pascucci, J. Ahrens, M. Hlawitschka, B. Hamann. In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2011 IEEE Visualization Conference, Vol. 17, No. 12, pp. 2088--2095. 2011.
PIDX: Efficient Parallel I/O for Multi-resolution Multi-dimensional Scientific Datasets|
S. Kumar, V. Vishwanath, P. Carns, B. Summa, G. Scorzelli, V. Pascucci, R. Ross, J. Chen, H. Kolla, R. Grout. In Proceedings of The IEEE International Conference on Cluster Computing, pp. 103--111. September, 2011.
Minimum Information about a Cardiac Electrophysiology Experiment (MICEE): Standardised reporting for model reproducibility, interoperability, and data sharing|
T.A. Quinn, S. Granite, M.A. Allessie, C. Antzelevitch, C. Bollensdorff, G. Bub, R.A.B. Burton, E. Cerbai, P.S. Chen, M. Delmar, D. DiFrancesco, Y.E. Earm, I.R. Efimov, M. Egger, E. Entcheva, M. Fink, R. Fischmeister, M.R. Franz, A. Garny, W.R. Giles, T. Hannes, S.E. Harding, P.J. Hunter, s, G. Iribe, J. Jalife, C.R. Johnson, R.S. Kass, I. Kodama, G. Koren, P. Lord, V.S. Markhasin, S. Matsuoka, A.D. McCulloch, G.R. Mirams, G.E. Morley, S. Nattel, D. Noble, S.P. Olesen, A.V. Panfilov, N.A. Trayanova, U. Ravens, S. Richard, D.S. Rosenbaum, Y. Rudy, F. Sachs, F.B. Sachse, D.A. Saint, U. Schotten, O. Solovyova, P. Taggart, L. Tung, A. Varrò, P.G. Volders, K. Wang, J.N. Weiss, E. Wettwer, E. White, R. Wilders, R.L. Winslow, P. Kohl. In Progress in Biophysics and Molecular Biology, Vol. 107, No. 1, Elsevier, pp. 4--10. October, 2011.
PubMed Central ID: PMC3190048
Cardiac experimental electrophysiology is in need of a well-defined Minimum Information Standard for recording, annotating, and reporting experimental data. As a step toward establishing this, we present a draft standard, called Minimum Information about a Cardiac Electrophysiology Experiment (MICEE). The ultimate goal is to develop a useful tool for cardiac electrophysiologists which facilitates and improves dissemination of the minimum information necessary for reproduction of cardiac electrophysiology research, allowing for easier comparison and utilisation of findings by others. It is hoped that this will enhance the integration of individual results into experimental, computational, and conceptual models. In its present form, this draft is intended for assessment and development by the research community. We invite the reader to join this effort, and, if deemed productive, implement the Minimum Information about a Cardiac Electrophysiology Experiment standard in their own work.
Keywords: Minimum Information Standard; Cardiac electrophysiology; Data sharing; Reproducibility; Integration; Computational modelling
Quantifying variability in radiation dose due to respiratory-induced tumor motion|
S.E. Geneser, J.D. Hinkle, R.M. Kirby, Bo Wang, B. Salter, S. Joshi. In Medical Image Analysis, Vol. 15, No. 4, pp. 640--649. 2011.
Using Hybrid Parallelism to improve memory use in Uintah|
Q. Meng, M. Berzins, J. Schmidt. In Proceedings of the TeraGrid 2011 Conference, Salt Lake City, Utah, ACM, July, 2011.
The Uintah Software framework was developed to provide an environment for solving fluid-structure interaction problems on structured adaptive grids on large-scale, long-running, data-intensive problems. Uintah uses a combination of fluid-flow solvers and particle-based methods for solids together with a novel asynchronous task-based approach with fully automated load balancing. Uintah's memory use associated with ghost cells and global meta-data has become a barrier to scalability beyond O(100K) cores. A hybrid memory approach that addresses this issue is described and evaluated. The new approach based on a combination of Pthreads and MPI is shown to greatly reduce memory usage as predicted by a simple theoretical model, with comparable CPU performance.
Keywords: Uintah, C-SAFE, parallel computing
Establishing Multiscale Models for Simulating Whole Limb Estimates of Electric Fields for Osseointegrated Implants|
B.M. Isaacson, J.G. Stinstra, R.D. Bloebaum, COL P.F. Pasquina, R.S. MacLeod. In IEEE Transactions on Biomedical Engineering, Vol. 58, No. 10, pp. 2991--2994. 2011.
PubMed ID: 21712151
PubMed Central ID: PMC3179554
Although the survival rates of warfighters in recent conflicts are among the highest in military history, those who have sustained proximal limb amputations may present additional rehabilitation challenges. In some of these cases, traditional prosthetic limbs may not provide adequate function for service members returning to an active lifestyle. Osseointegration has emerged as an acknowledged treatment for those with limited residual limb length and those with skin issues associated with a socket together. Using this technology, direct skeletal attachment occurs between a transcutaneous osseointegrated implant (TOI) and the host bone, thereby eliminating the need for a socket. While reports from the first 100 patients with a TOI have been promising, some rehabilitation regimens require 12-18 months of restricted weight bearing to prevent overloading at the bone-implant interface. Electrically induced osseointegration has been proposed as an option for expediting periprosthetic fixation and preliminary studies have demonstrated the feasibility of adapting the TOI into a functional cathode. To assure safe and effective electric fields that are conducive for osseoinduction and osseointegration, we have developed multiscale modeling approaches to simulate the expected electric metrics at the bone--implant interface. We have used computed tomography scans and volume segmentation tools to create anatomically accurate models that clearly distinguish tissue parameters and serve as the basis for finite element analysis. This translational computational biological process has supported biomedical electrode design, implant placement, and experiments to date have demonstrated the clinical feasibility of electrically induced osseointegration.
IMPICE Method for Compressible Flow Problems in Uintah|
L.T. Tran, M. Berzins. In International Journal For Numerical Methods In Fluids, Note: Published online 20 July, 2011.
Scalable parallel regridding algorithms for block-structured adaptive mesh renement|
J. Luitjens, M. Berzins. In Concurrency And Computation: Practice And Experience, Vol. 23, No. 13, John Wiley & Sons, Ltd., pp. 1522--1537. 2011.
ZAPP – A management framework for distributed visualization systems|
G. Tamm, A. Schiewe, J. Krüger. In Proceedings of CGVCVIP 2011 : IADIS International Conference on Computer Graphics, Visualization, Computer Vision And Image Processing, pp. (accepted). 2011.
Real-time magnetic resonance imaging-guided radiofrequency atrial ablation and visualization of lesion formation at 3 Tesla|
G.R. Vergara, S. Vijayakumar, E.G. Kholmovski, J.J. Blauer, M.A. Guttman, C. Gloschat, G. Payne, K. Vij, N.W. Akoum, M. Daccarett, C.J. McGann, R.S. Macleod, N.F. Marrouche. In Heart Rhythm, Vol. 8, No. 2, pp. 295--303. 2011.
PubMed ID: 21034854
Association of left atrial fibrosis detected by delayed-enhancement magnetic resonance imaging and the risk of stroke in patients with atrial fibrillation|
M. Daccarett, T.J. Badger, N. Akoum, N.S. Burgon, C. Mahnkopf, G.R. Vergara, E.G. Kholmovski, C.J. McGann, D.L. Parker, J. Brachmann, R.S. Macleod, N.F. Marrouche. In Journal of the American College of Cardiology, Vol. 57, No. 7, pp. 831--838. 2011.
PubMed ID: 21310320
MRI of the left atrium: predicting clinical outcomes in patients with atrial fibrillation|
M. Daccarett, C.J. McGann, N.W. Akoum, R.S. MacLeod, N.F. Marrouche. In Expert Review of Cardiovascular Therapy, Vol. 9, No. 1, pp. 105--111. 2011.
PubMed ID: 21166532
Finite Element Based Discretization and Regularization Strategies for 3D Inverse Electrocardiography|
D. Wang, R.M. Kirby, C.R. Johnson. In IEEE Transactions for Biomedical Engineering, Vol. 58, No. 6, pp. 1827--1838. 2011.
PubMed ID: 21382763
PubMed Central ID: PMC3109267
We consider the inverse electrocardiographic problem of computing epicardial potentials from a body-surface potential map. We study how to improve numerical approximation of the inverse problem when the finite-element method is used. Being ill-posed, the inverse problem requires different discretization strategies from its corresponding forward problem. We propose refinement guidelines that specifically address the ill-posedness of the problem. The resulting guidelines necessitate the use of hybrid finite elements composed of tetrahedra and prism elements. Also, in order to maintain consistent numerical quality when the inverse problem is discretized into different scales, we propose a new family of regularizers using the variational principle underlying finite-element methods. These variational-formed regularizers serve as an alternative to the traditional Tikhonov regularizers, but preserves the L2 norm and thereby achieves consistent regularization in multiscale simulations. The variational formulation also enables a simple construction of the discrete gradient operator over irregular meshes, which is difficult to define in traditional discretization schemes. We validated our hybrid element technique and the variational regularizers by simulations on a realistic 3-D torso/heart model with empirical heart data. Results show that discretization based on our proposed strategies mitigates the ill-conditioning and improves the inverse solution, and that the variational formulation may benefit a broader range of potential-based bioelectric problems.
A Diffusion Approach to Network Localization|
Y. Keller, Y. Gur. In IEEE Transactions on Signal Processing, Vol. 59, No. 6, pp. 2642--2654. 2011.