Suran Galappaththige
I am a Research Fellow at U.S. Food and Drug Administration, Silver Spring, Maryland, USA working on mathematical modeling and simulation of cardiac electrical activity.
I received my PhD in Biomedical Sciences: Medical Physics from Oakland University, Rochester, Michigan, USA.
Education
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Ph.D. Biomedical Sciences: Medical PhysicsDepartment of Physics, Oakland University, Michigan, USA, 2017Advisor: Prof. Bradley J. Roth
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M.Sc. Physics of MaterialsPostgraduate Institute of Science, University Peradeniya, Peradeniya, Sri Lanka, 2010Advisor: Prof. Piyasiri Ekanayake
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B.Sc. (Hons) Physics, Applied Mathematics & Pure Mathematics
Publications
Journal Publications
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Data-Driven Uncertainty Quantification for Cardiac Electrophysiological Models: Impact of Physiological Variability on Action Potential and Spiral Wave DynamicsFrontiers in physiology, 2020.
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Effect of heart structure on ventricular fibrillation in the rabbit: A simulation studyFrontiers in physiology, 2019.
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Modeling bipolar stimulation of cardiac tissueChaos: An Interdisciplinary Journal of Nonlinear Science, 2017.
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Cardiac strength-interval curves calculated using the bidomain model with a parsimonious ionic currentPloS one, 2017.
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Electrical Pacing of Cardiac Tissue Including Potassium Inward RectificationPloS one, 2015.
Conference Publications
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Acute Effects of Nonexcitatory Electrical Stimulation During Systole in Human-induced Pluripotent Stem Cell Derived CardiomyocytesBasic Cardiovascular Sciences Scientific Sessions, Emerging Opportunities in Cardiovascular Diseases. American Heart Association, Chicago, USA (virtual event, contributing author). July, 2020.
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Impact of Parameter Uncertainty on Cardiac Electrophysiological Model PredictionsVerification & Validation Symposium, American Society of Mechanical Engineers. USA (virtual event, contributing author). May, 2020.
Poster Presentations & Talks
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Cardiac Modeling and SimulationDivision of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA (research talk). October, 2019.
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Strength – Interval Curves using a Minimal Ionic Model and the Bidomain Model.Biology and Medicine through Mathematics Conference, Virginia Commonwealth University, Richmond, Virginia, USA (poster presentation). May, 2016.
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Strength – Interval Curves using a Minimal Ionic Model and the Bidomain Model.Graduate Student Research Conference, Oakland University, Michigan, USA (research talk). March, 2016.
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Electrical pacing of cardiac tissue including potassium inward rectification.Sigma XI Research Festival. Oakland University, Rochester, Michigan, USA (poster presentation). March, 2015.
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Electrical pacing of cardiac tissue including potassium inward rectification.Annual Conference of Michigan Academy of Science Arts and Letters. Andrews University, Berrien Springs, Michigan, USA. (poster presentation). March, 2015.
Projects
A patient-specific model (PSM) is a computational model that has been personalized to represent a particular patient. Numerous devices that construct PSMs have already been cleared/approved by CDRH (used for e.g., non-invasive coronary artery disease detection; non-invasive acquisition of heart surface electrophysiological maps; and planning neurointerventional device deployment). In silico clinical trials (ISCTs) are an approach where virtual cohorts of patients are used to assess performance of a medical device. ISCTs are already essentially used in regulatory submissions where real clinical trials would be unethical (e.g., studying implant heating during MRI), and have the potential to revolutionize approval of devices by reducing the size of real clinical trials. In this project we will evaluate the current methods used for patient-specific modeling and in silico clinical trial approaches used for cardiovascular applications.
The complex spatio-temporal dynamics of arrhythmia conditions on both ventricle and atria are studied by the modeling and simulation techniques. This enables visualization and analysis of electrical activity throughout the full three-dimensional heart at a resolution nearly equal to the cellular level. Modeling and simulation allow us to control factors that would be impossible in a clinical setting. We are currently using 3D atria and bi-ventricular mesh models for the simulation of electrical activity after a stimulus using the finite elemental analysis method by using CHASTE cardiac solver. The goal of this project is to develop a computational model of electrical wave propagation throughout the heart in which the mechanism and location of the "virtual arrhythmias" are known, which can be used to evaluate the accuracy and robustness of devices using scientifically rigorous methodology.
Computational modeling of cardiac electrophysiology (EP) has recently transitioned from uniquely scientific research approach to include clinical applications. These clinical models have a range of applications, including medical device assessment, drug safety assessment and serving as clinical decision-making tools. To ensure the reliability of clinical or regulatory decisions made using cardiac EP models, it is vital to assess the uncertainty in model predictions. My contribution to this project is to run simulations and analyze the outputs of simulations for parameter estimation.
Cardiac contractility modulation (CCM) is a cardiac therapy whereby nonexcitatory electrical stimulations are delivered to the heart during the absolute refractory period of the cardiac cycle. My contribution to this project is to analyze large sets of images to measure cardiac contractility by developing code to automate the measurement of cardiomyocytes.
Cardiac tissue is modeled as a two-dimensional bidomain. The bidomain model describes the electrical properties of the extracellular space and the intracellular space as a pair of coupled partial differential equations and the active properties of the cardiac tissue is described by several ion currents. The coupled partial differential equations are solved numerically to study the behavior of the tissue.
Examined the degradation of articular cartilage using micro-MRI. Setting up experiments, acquiring images and analyzing images. Analysis of T1, T2 and T1ρ relaxation times in different zones of the cartilage.
The physical properties of a polymer gel, its elasticity, permeability, dangling ends, diffusion of connected strands and foreign particles produce measurable density fluctuations that can be measured using Dynamic Light Scattering (DLS). Different modes of relaxation in the polymer gel can be measured using the noninvasive technique.
Skills
My graduate research work and current postdoctoral research work are centered around the mathematical and computational modeling and simulation of cardiac electrophysiology. My research is interdisciplinary in nature and depends heavily on Mathematics, Physics, Biology and Computer programming. Over the years, I have gained extensive knowledge on mathematical modeling and simulation of biological systems.
Mathematical Modeling and Simulation
For my dissertation research, I used finite difference method to model and simulate cardiac electrical activity on a two dimensional (2D) tissue. We used the bidomain model with parsimonious ionic current model to simulate the cardiac electrical activity resulting from a stimulus applied on to the tissue, using a computer program written in Fortran. Due to the higher number of ordinary differential equations (ODEs) and partial differential equations (PDEs) that we need to solve in each node in the tissue of size 1cm by 1cm with a space step of 0.005 cm parallel to the fiber direction and a space step of 0.002 cm perpendicular to the fiber direction with a time step of 1 μs, demands speed and the ability to handle large amount of data. Fortran is an ideal programming language for mathematically demanding calculations.
My postdoctoral work involves three dimensional (3D) modeling and simulation of whole heart. We used “CHASTE” for computational modeling of the 3D models. Chaste is a parallel cardiac solver written in C++ for computationally demanding simulations that use finite elemental analysis method.
Coursework
I have taken numerous coursework related to physics, mathematics and biology. Some of them are given below.
PhD coursework
Radiation Biophysics, Modeling Complex Systems, Bioelectric Phenomena, Nuclear Magnetic Resonance, Medical Physics, Theoretical Physics, Quantum Physics, Design & Analysis of Algorithms, Ethics and Practices of Science
MSc coursework
Mathematical methods and Computational methods, Electron theory of solids, Semiconductors, Ceramic materials, Polymers, Material characterization techniques, Nuclear materials.
BSc coursework
General Physics, Modern physics, AC Theory, Waves and Vibrations, Thermal Physics, Differential equations, Numerical methods, Mathematical modeling in Economics, Finance and Insurance, Regression and time series, Environmental physics, Health physics.
Software Skills
Scientific computing: Finite difference methods, Finite element analysis, Scipy, Numpy, Chaste
Image analysis: Digital image analysis methods using Python and Parallel Python
Programming and Scripting Languages: Fortran, C++, Python, MATLAB
Operating Systems: Ubuntu, Windows
Other: Bash Scripting, Git, LaTex, Meshtool, Meshlab, GIMP, Inkscape
Certification
Introduction to Data Science in Python
Teaching
There is nothing more exciting to a teacher than the moment his student show signs of joy in understanding what he explains to his students in a class. I have been lucky enough to witness these awesome moments over and over. Throughout my teaching career, which spans nearly a decade before I started my doctoral studies, to when I worked as a teaching assistant in the Department of Physics at Oakland University, every day that I teach either in a class room or in a physics lab is day full of enjoyment and excitement. I love teaching, and my love for science and my passion to share knowledge drives me to teaching. I have always looked up to the profession of teaching as highly noble. I have been inspired by my teachers whom I have learnt from throughout my school days and university years, who have dedicated themselves to teaching and to their students.
I began my teaching career just after my bachelor’s degree in early 2001, when I joined the Physics Department of the University of Colombo as a temporary demonstrator where, I taught electronics labs to undergraduate students. Since then I have worked in various institutions as a teacher in Sri Lanka and abroad in secondary and postsecondary level.