Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia

Reduced blood flow in the coronary arteries can lead to damaged heart tissue (myocardial ischaemia). Although one method for detecting myocardial ischaemia involves changes in the ST segment of the electrocardiogram, the relationship between these changes and subendocardial ischaemia is not fully understood. In this study, we modelled ST-segment epicardial potentials in a slab model of cardiac ventricular tissue, with a central ischaemic region, using the bidomain model, which considers conduction longitudinal, transverse and normal to the cardiac fibres. We systematically quantified the effect of uncertainty on the input parameters, fibre rotation angle, ischaemic depth, blood conductivity and six bidomain conductivities, on outputs that characterise the epicardial potential distribution. We found that three typical types of epicardial potential distributions (one minimum over the central ischaemic region, a tripole of minima, and two minima flanking a central maximum) could all occur for a wide range of ischaemic depths. In addition, the positions of the minima were affected by both the fibre rotation angle and the ischaemic depth, but not by changes in the conductivity values. We also showed that the magnitude of ST depression is affected only by changes in the longitudinal and normal conductivities, but not by the transverse conductivities.

[1]  Joakim Sundnes,et al.  Simulation of ST segment changes during subendocardial ischemia using a realistic 3-D cardiac geometry , 2005, IEEE Transactions on Biomedical Engineering.

[2]  D. Xiu Efficient collocational approach for parametric uncertainty analysis , 2007 .

[3]  P. Hunter,et al.  Laminar structure of the heart: a mathematical model. , 1997, The American journal of physiology.

[4]  J. Stinstra,et al.  Using models of the passive cardiac conductivity and full heart anisotropic bidomain to study the epicardial potentials in ischemia , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  J. Stinstra,et al.  On the Passive Cardiac Conductivity , 2005, Annals of Biomedical Engineering.

[6]  T. Opthof,et al.  Injury current and gradients of diastolic stimulation threshold, TQ potential, and extracellular potassium concentration during acute regional ischemia in the isolated perfused pig heart. , 1991, Circulation research.

[7]  J. Stinstra,et al.  Mechanisms of ischemia-induced ST-segment changes. , 2005, Journal of electrocardiology.

[8]  Barbara M. Johnston,et al.  Six Conductivity Values to Use in the Bidomain Model of Cardiac Tissue , 2016, IEEE Transactions on Biomedical Engineering.

[9]  Peter R. Johnston,et al.  Defibrillation thresholds: A generalised polynomial chaos study , 2014, Computing in Cardiology 2014.

[10]  Peter R. Johnston,et al.  The effect of conductivity values on ST segment shift in subendocardial ischaemia , 2003, IEEE Transactions on Biomedical Engineering.

[11]  L. Clerc Directional differences of impulse spread in trabecular muscle from mammalian heart. , 1976, The Journal of physiology.

[12]  Rob S. MacLeod,et al.  The role of reduced left ventricular, systolic blood volumes in ST segment potentials overlying diseased tissue of the ischemic heart , 2016, 2016 Computing in Cardiology Conference (CinC).

[13]  Leslie Tung,et al.  A bi-domain model for describing ischemic myocardial d-c potentials , 1978 .

[14]  Barbara M. Johnston,et al.  The effect of conductivity values on activation times and defibrillation thresholds , 2016, 2016 Computing in Cardiology Conference (CinC).

[15]  R. M. Arthur,et al.  Effect of inhomogeneities on the apparent location and magnitude of a cardiac current dipole source. , 1970, IEEE transactions on bio-medical engineering.

[16]  F. Trelles,et al.  Measurement of myocardial conductivities with a four-electrode technique in the frequency domain , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[17]  Bruce H Smaill,et al.  Three Distinct Directions of Intramural Activation Reveal Nonuniform Side-to-Side Electrical Coupling of Ventricular Myocytes , 2009, Circulation. Arrhythmia and electrophysiology.

[18]  Anthony O'Hagan,et al.  Diagnostics for Gaussian Process Emulators , 2009, Technometrics.

[19]  Mark Potse,et al.  The role of extracellular potassium transport in computer models of the ischemic zone , 2007, Medical & Biological Engineering & Computing.

[20]  Boyce E. Griffith,et al.  Deriving Macroscopic Myocardial Conductivities by Homogenization of Microscopic Models , 2009, Bulletin of mathematical biology.

[21]  Bruce H Smaill,et al.  Laminar Arrangement of Ventricular Myocytes Influences Electrical Behavior of the Heart , 2007, Circulation research.

[22]  J. Ross,et al.  Fiber Orientation in the Canine Left Ventricle during Diastole and Systole , 1969, Circulation research.

[23]  Pras Pathmanathan,et al.  Uncertainty and variability in models of the cardiac action potential: Can we build trustworthy models? , 2016, Journal of molecular and cellular cardiology.

[24]  Peter R. Johnston,et al.  The importance of anisotropy in modeling ST segment shift in subendocardial ischaemia , 2001, IEEE Transactions on Biomedical Engineering.

[25]  R. Coronel,et al.  The effect of lesion size and tissue remodeling on ST deviation in partial-thickness ischemia. , 2007, Heart rhythm.

[26]  Kevin Burrage,et al.  Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm , 2016, Progress in biophysics and molecular biology.

[27]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[28]  David Kilpatrick,et al.  Mechanisms of ST change in partial thickness ischemia. , 2003, Journal of electrocardiology.

[29]  Olivier P. Le Maître,et al.  Polynomial chaos expansion for sensitivity analysis , 2009, Reliab. Eng. Syst. Saf..

[30]  A. M. Scher,et al.  Influence of Cardiac Fiber Orientation on Wavefront Voltage, Conduction Velocity, and Tissue Resistivity in the Dog , 1979, Circulation research.

[31]  Jeroen G Stinstra,et al.  Mechanism for ST Depression Associated with Contiguous Subendocardial Ischemia , 2004, Journal of cardiovascular electrophysiology.

[32]  M. Kontos,et al.  Emergency department and office-based evaluation of patients with chest pain. , 2010, Mayo Clinic proceedings.

[33]  A. M. Scher,et al.  Effect of Tissue Anisotropy on Extracellular Potential Fields in Canine Myocardium in Situ , 1982, Circulation research.

[34]  Hervé Delingette,et al.  Human Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population , 2012, IEEE Transactions on Medical Imaging.

[35]  D Durrer,et al.  Mechanism and Time Course of S‐T and T‐Q Segment Changes during Acute Regional Myocardial Ischemia in the Pig Heart Determined by Extracellular and Intracellular Recordings , 1978, Circulation research.

[36]  Mark Strong,et al.  Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator , 2015, PloS one.

[37]  J. Stinstra,et al.  The Effect of Conductivity on ST-Segment Epicardial Potentials Arising from Subendocardial Ischemia , 2005, Annals of Biomedical Engineering.

[38]  Pierre Savard,et al.  Measurement of myocardial conductivities with an eight-electrode technique in the frequency domain , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[39]  R. Lux,et al.  Effect of Myocardial Fiber Direction on Epicardial Potentials , 1994, Circulation.

[40]  Shibaji Shome,et al.  Modelling passive cardiac conductivity during ischaemia , 2005, Medical and Biological Engineering and Computing.

[41]  Wanda Krassowska,et al.  Theoretical versus experimental estimates of the effective conductivities of cardiac muscle , 1992, Proceedings Computers in Cardiology.

[42]  Dongbin Xiu,et al.  High-Order Collocation Methods for Differential Equations with Random Inputs , 2005, SIAM J. Sci. Comput..

[43]  B. Roth Nonsustained Reentry Following Successive Stimulation of Cardiac Tissue Through a Unipolar Electrode , 1997, Journal of cardiovascular electrophysiology.

[44]  Jeremy E. Oakley,et al.  Bayesian sensitivity analysis of a nonlinear finite element model , 2012 .

[45]  E. Sobie Parameter sensitivity analysis in electrophysiological models using multivariable regression. , 2009, Biophysical journal.

[46]  Peter R Johnston,et al.  A finite volume method solution for the bidomain equations and their application to modelling cardiac ischaemia , 2010, Computer methods in biomechanics and biomedical engineering.

[47]  A. O'Hagan,et al.  Probabilistic sensitivity analysis of complex models: a Bayesian approach , 2004 .

[48]  F B Sachse,et al.  Estimating Intracellular Conductivity Tensors from Confocal Microscopy of Rabbit Ventricular Tissue , 2013, Biomedizinische Technik. Biomedical engineering.

[49]  The effect of ischaemic region shape on epicardial potential distributions in transient models of cardiac tissue , 2012 .

[50]  P. Savard,et al.  Extracellular Measurement of Anisotropic Bidomain Myocardial Conductivities. I. Theoretical Analysis , 2001, Annals of Biomedical Engineering.

[51]  Robert Michael Kirby,et al.  Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity , 2008, IEEE Transactions on Biomedical Engineering.

[52]  Bradley J. Roth,et al.  An S1 gradient of refractoriness is not essential for reentry induction by an S2 stimulus , 2000, IEEE Trans. Biomed. Eng..

[53]  S. Rush,et al.  Resistivity of Body Tissues at Low Frequencies , 1963, Circulation research.

[54]  Robert M. Kirby,et al.  Cardiac Position Sensitivity Study in the Electrocardiographic Forward Problem Using Stochastic Collocation and Boundary Element Methods , 2011, Annals of Biomedical Engineering.

[55]  Darren A Hooks,et al.  Myocardial segment-specific model generation for simulating the electrical action of the heart , 2007, Biomedical engineering online.

[56]  Felipe Aguel,et al.  Computer simulations of cardiac defibrillation: a look inside the heart , 2002 .

[57]  D Kilpatrick,et al.  Source of electrocardiographic ST changes in subendocardial ischemia. , 1998, Circulation research.

[58]  Arun V. Holden,et al.  A Quantitative Comparison of the Myocardial Fibre Orientation in the Rabbit as Determined by Histology and by Diffusion Tensor-MRI , 2009, FIMH.

[59]  Bradley J. Roth,et al.  The electrical potential produced by a strand of cardiac muscle: A bidomain analysis , 2006, Annals of Biomedical Engineering.

[60]  B. Roth Electrical conductivity values used with the bidomain model of cardiac tissue , 1997, IEEE Transactions on Biomedical Engineering.