Scaling of Ventricular Turbulence Phase Singularities Numerical Implementation Model Construction (cont.) Conclusions and Future Work  We have constructed.

Slides:



Advertisements
Similar presentations
Spiral-wave Turbulence and its Control in Excitable Media like Cardiac Tissue Microsoft External Research Initiative.
Advertisements

Wavefront-based models for inverse electrocardiography Alireza Ghodrati (Draeger Medical) Dana Brooks, Gilead Tadmor (Northeastern University) Rob MacLeod.
Point-wise Discretization Errors in Boundary Element Method for Elasticity Problem Bart F. Zalewski Case Western Reserve University Robert L. Mullen Case.
Scroll waves meandering in a model of an excitable medium Presenter: Jianfeng Zhu Advisor: Mark Alber.
MUTAC Review April 6-7, 2009, FNAL, Batavia, IL Mercury Jet Target Simulations Roman Samulyak, Wurigen Bo Applied Mathematics Department, Stony Brook University.
Session: Computational Wave Propagation: Basic Theory Igel H., Fichtner A., Käser M., Virieux J., Seriani G., Capdeville Y., Moczo P.  The finite-difference.
Systems Biology talk July Systems Biology of the Heart Richard Clayton.
Ionic Mechanisms of Propagation in Cardiac Tissue: Roles of the Sodium and L-type Calcium Currents During Reduced Excitability and Decreased Gap Junction.
Spiral waves meandering in a model of an excitable medium Presenter: Mike Malatt Phil McNicholas Jianfeng Zhu.
Seashells. This presentation presents a method for modeling seashells. Why seashells you ask ? Two main reasons : The beauty of shells invites us to construct.
The Workshop Project Understanding Spiral Waves. The refractory period Excitable systems can sustain spiral waves as well as plain waves This is due to.
From Idealized to Fully- Realistic Geometrical modeling Scaling of Ventricular Turbulence Phase Singularities Numerical Implementation Model Construction.
A guide to modelling cardiac electrical activity in anatomically detailed ventricles By: faezeh heydari khabbaz.
Gating Modeling of Ion Channels Chu-Pin Lo ( 羅主斌 ) Department of Applied Mathematics Providence University 2010/01/12 (Workshop on Dynamics for Coupled.
Transport of Pharmocokinetic Agents in the Myocardium Xianfeng Song Sima Setayeshgar Feb. 16, 2004.
Computational Biology, Part E Basic Principles of Computer Graphics Robert F. Murphy Copyright  1996, 1999, 2000, All rights reserved.
OPTIMIZATION OF FUNCTIONAL BRAIN ROIS VIA MAXIMIZATION OF CONSISTENCY OF STRUCTURAL CONNECTIVITY PROFILES Dajiang Zhu Computer Science Department The University.
Physics of the Heart: From the macroscopic to the microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
August 14 th, 2012 Comparison of compressible explicit density-based and implicit pressure-based CFD methods for the simulation of cavitating flows Romuald.
Preventing Sudden Cardiac Death Rob Blake NA Seminar
Spiral and Scroll Waves in Excitable Media: Cardiological Applications A Calculus III Honors Project by David Hausner And Katrina McAlpin.
Numerical simulations of thermal counterflow in the presence of solid boundaries Andrew Baggaley Jason Laurie Weizmann Institute Sylvain Laizet Imperial.
Luke Bloy1, Ragini Verma2 The Section of Biomedical Image Analysis
Introduction to Level Set Methods: Part II
Transport Through the Myocardium of Pharmocokinetic Agents Placed in the Pericardial Sac: Insights From Physical Modeling Xianfeng Song, Department of.
Doc.: IEEE /0431r0 Submission April 2009 Alexander Maltsev, Intel CorporationSlide 1 Polarization Model for 60 GHz Date: Authors:
The Role of the Bidomain Model of Cardiac Tissue in the Dynamics of Phase Singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana.
New Techniques for Visualizing and Evaluating Left Ventricular Performance Burkhard Wünsche 1 & Alistair Young 2 1 Division for Biomedical Imaging & Visualization.
Physics of the Heart: From the macroscopic to the microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
Role of the Bidomain Model of Cardiac Tissue in the Dynamics of Phase Singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana University,
The role of the bidomain model of cardiac tissue in the dynamics of phase singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana.
Result Mathematical Modeling The key processes  Substrate transport across boundary layer between pericardial sac and myocardium, described by the parameter.
Role of the Bidomain Model of Cardiac Tissue in the Dynamics of Phase Singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana University,
Advisor: Sima Setayeshgar
1 Spatially adaptive Fibonacci grids R. James Purser IMSG at NOAA/NCEP Camp Springs, Maryland, USA.
Numerical Implementation Diffusion Tensor Governing Equations From Idealized to Fully- Realistic Geometrical modeling Phase Singularities Model Construction.
Physics of the Heart: From the macroscopic to the microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
Numerical Results Mathematical Modeling Key Biophysical Processes Substrate transport across boundary layer between pericardial sac and myocardium, described.
Result Mathematical Modeling The key processes  Substrate transport across boundary layer between pericardial sac and myocardium, described by the parameter.
Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Department of Physics, Indiana University.
Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Department of Physics, Indiana University.
Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Department of Physics, Indiana University.
Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Department of Physics, Indiana University.
Optimization of planar pixel detector. T. Habermann Planar pixel detectors L W H ground U.
Physics of Heart: From macroscopic to microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
Transport of Pharmocokinetic Agents in the Myocardium Xianfeng Song, Department of Physics, IUB Keith L. March, IUPUI Medical School Sima Setayeshgar,
ASCI/Alliances Center for Astrophysical Thermonuclear Flashes An Interface Propagation Model for Reaction-Diffusion Advection Adam Oberman An Interface.
Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Department of Physics, Indiana University.
Physics of Heart: From macroscopic to microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
Physics of Heart: From macroscopic to microscopic Xianfeng Song Advisor: Sima Setayeshgar January 9, 2007.
Role of the Bidomain Model of Cardiac Tissue in the Dynamics of Phase Singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana University,
The Role of the Bidomain Model of Cardiac Tissue in the Dynamics of Phase Singularities Jianfeng Lv and Sima Setayeshgar Department of Physics, Indiana.
ECE 383 / ME 442 Fall 2015 Kris Hauser
Advisor: Sima Setayeshgar
Advisor: Sima Setayeshgar
Break-up (>= 2 filaments)
Mathematical modeling of cryogenic processes in biotissues and optimization of the cryosurgery operations N. A. Kudryashov, K. E. Shilnikov National Research.
NUMERICAL INVESTIGATIONS OF FINITE DIFFERENCE SCHEMES
Break-up (>= 2 filaments)
Xianfeng Song, Department of Physics, Indiana University
Xianfeng Song[1], Keith L. March[2], Sima Setayeshgar[1]
Xianfeng Song[1], Keith L. March[2], Sima Setayeshgar[1]
W.F. Witkowksi, et al., Nature 392, 78 (1998)
Break-up (>= 2 filaments)
Volume 95, Issue 2, Pages (July 2008)
Break-up (>= 2 filaments)
Low Order Methods for Simulation of Turbulence in Complex Geometries
Transport of Pharmocokinetic Agents in the Myocardium
Break-up (>= 2 filaments)
Why Is Alternans Indeterminate?
Presentation transcript:

Scaling of Ventricular Turbulence Phase Singularities Numerical Implementation Model Construction (cont.) Conclusions and Future Work  We have constructed and implemented a minimally realistic fiber architecture model of the left ventricle for studying electrical wave propagation in the three dimensional myocardium.  Our model adequately addresses the geometry and fiber architecture of the LV, as indicated by the agreement of filament dynamics with that from fully realistic geometrical models.  Our model is computationally more tractable, allowing reliable numerical studies. It is easily parallelizable and has good scalability.  As such, it is more feasible for incorporating  Realistic electrophysiology  Biodomain description of tissue  Electromechanical coupling Parallelization Numerical Convergence Model Construction Motivation Ventricular fibrillation (VF) is the main cause of sudden cardiac death in industrialized nations, accounting for 1 out of 10 deaths.Strong experimental evidence suggests that self- sustained waves of electrical wave activity in cardiac tissue are related to fatal arrhythmias. Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle Xianfeng Song, Sima Setayeshgar Department of Physics, Indiana University W.F. Witkowksi, et al., Nature 392, 78 (1998) Patch size: 5 cm x 5 cm Time spacing: 5 msec Mechanisms that generate and sustain VF are poorly understood. One conjectured mechanism is: Breakdown of a single spiral (scroll) wave into a disordered state, resulting from various mechanisms of spiral wave instability. From idealized to fully realistic geometrical modeling Rectangular slabAnatomical canine ventricular model J.P. Keener, et al., in Cardiac Electrophysiology, eds. D. P. Zipes et al. (1995) Courtesy of A. V. Panfilov, in Physics Today, Part 1, August 1996 Minimally realistic model of LV for studying electrical wave propagation in three dimensional anisotropic myocardium that adequately addresses the role of geometry and fiber architecture and is:  Simpler and computationally more tractable than fully realistic models  Easily parallelizable and with good scalability  More feasible for incorporating realistic electrophysiology, electromechanical coupling, Fibers on a nested pair of surfaces in the LV, from C. E. Thomas, Am. J. Anatomy (1957). Early dissection results revealed nested ventricular fiber surfaces, with fibers given approximately by geodesics on these surfaces. Our model  Adopted Nested cone geometry fiber surfaces  the fiber paths are both geodesics on fiber surfaces and circumferential at midwall. inner surfaceouter surface subject to: Fiber trajectory: Transmembrane potential propagation C m : capacitance per unit area of membrane D: diffusion tensor u: transmembrane potential I m : transmembrane current v: gate variable Parameters: a=0.1, m 1 =0.07, m 2 =0.3, k=8, e=0.01, C m =1 Diffusion Tensor Local CoordinateLab Coordinate Transformation matrix R The communication can be minimized when parallelized along azimuthal direction. Computational results show the model has a very good scalability. CPUsSpeed up ± ± ± ± ± 0.85 Tips and filaments are phase singularities that act as organizing centers for spiral (2D) and scroll (3D) dynamics, respectively, offering a way to quantify and simplify the full spatiotemporal dynamics. Finding all tips Add current tip into a new filament, marked as the head of this filament Find the closest unmarked tip End Choose an unmarked tip as current tip Is the distance smaller than a certain threshold? Set the closest tip as current tip Mark the current tip set reversed=0 Add current tip into current filament Set the head of current filament as current tip Is revered=0? Are there any unmarked tips? Set reversed=1 Definition: Distance between two tips (1)If two tips are not on a same fiber surface or on adjacent surfaces, the distance is defined to be infinity (2)Otherwise, the distance is the distance along the fiber surface Yes No Yes No t = 2 t = 999 The results for filament number agree to within error bars for dr=0.7 and dr=0.5. The result for dr=1.1 is slightly off, which could be due to the filament finding algorithm. The computation time for dr=0.7 for one wave period in a normal heart size is less than 1 hour of CPU time using FHN-like electrophysiological model. Crossection along azimuthal direction Fiber trajectories on nested pair of conical surfaces Fiber path equation Governing Equations Transmembrane current, Im, described by simplified FitzHugh-Nagumo type dynamics  Working in spherical coordinates, with the boundaries of the computational domain described by two nested cones, is equivalent to computing in a box.  Standard centered finite difference scheme is used to treat the spatial derivatives, along with first-order explicit Euler time-stepping. Log(total filament length) and Log(filament number) versus Log(heart size) The average filament length, normalized by average heart thickness, versus heart size These results are in agreement with those obtained with the fully realistic canine anatomical model, using the same electrophysiology. A. V. Panfilov, Phys. Rev. E 59, R6251 (1999) Filament finding algorithm The filament finding results. The left pictures show the simulation at time=2 and time=999. The right pictures show the filament finding results, corresponding to the scroll waves.