skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study

Abstract

Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored. Thus, this study aimed to determine the sensitivity of the QRS complex of the ECG to the anatomical location and regional number of PMJs. The QRS complex was simulated using an image-based human torso and biventricular model, and cardiac electrophysiology was simulated using Cardioid. The PMJs were modeled as discrete current injection stimuli, and the location and number of stimuli were varied within initial activation regions based on published experiments. Results indicate that the QRS complex features were most sensitive to the presence or absence of four “seed” stimuli, and adjusting locations of nearby “regional” stimuli provided finer tuning. Decreasing number of regional stimuli by an order of magnitude resulted in virtually no change in the QRS complex. Thus, a minimalmore » 12-stimuli configuration was identified that resulted in physiological excitation, defined by QRS complex feature metrics and ventricular excitation pattern. In conclusion, overall, the sensitivity results suggest that parameterizing PMJ location, rather than number, be given significantly higher priority in future studies creating personalized ventricular models from patient-derived ECGs.« less

Authors:
 [1];  [1];  [2];  [3];  [1];  [4]; ORCiD logo [1];  [1];  [1];  [1];  [2];  [5];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of California, San Diego, CA (United States)
  3. Univ. of California, Davis, CA (United States)
  4. Harvard Medical School, Boston, MA (United States); Brigham and Women’s Hospital, Boston, MA (United States)
  5. Univ. of California, San Diego, CA (United States); VA San Diego Healthcare System, San Diego, CA (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE; National Institutes of Health (NIH)
OSTI Identifier:
1463971
Grant/Contract Number:  
AC05-00OR22725; AC52-07NA27344; P41 GM103545-18; HL105242; HL111197; HL61795; HG007690; HL122199; HL126273; GM107618; FG02-97ER25308; 5 T32 HL 7444-32
Resource Type:
Accepted Manuscript
Journal Name:
Cardiovascular Engineering and Technology
Additional Journal Information:
Journal Volume: 9; Journal Issue: 3; Journal ID: ISSN 1869-408X
Publisher:
Springer Nature
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; Human ventricular excitation; Sensitivity analysis; Electrocardiogram; Patient-specific modeling; Computational electrophysiology; Bundle branch block

Citation Formats

Cranford, Jonathan P., O’Hara, Thomas J., Villongco, Christopher T., Hafez, Omar M., Blake, Robert C., Loscalzo, Joseph, Fattebert, Jean-Luc, Richards, David F., Zhang, Xiaohua, Glosli, James N., McCulloch, Andrew D., Krummen, David E., Lightstone, Felice C., and Wong, Sergio E. Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study. United States: N. p., 2018. Web. doi:10.1007/s13239-018-0347-0.
Cranford, Jonathan P., O’Hara, Thomas J., Villongco, Christopher T., Hafez, Omar M., Blake, Robert C., Loscalzo, Joseph, Fattebert, Jean-Luc, Richards, David F., Zhang, Xiaohua, Glosli, James N., McCulloch, Andrew D., Krummen, David E., Lightstone, Felice C., & Wong, Sergio E. Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study. United States. doi:10.1007/s13239-018-0347-0.
Cranford, Jonathan P., O’Hara, Thomas J., Villongco, Christopher T., Hafez, Omar M., Blake, Robert C., Loscalzo, Joseph, Fattebert, Jean-Luc, Richards, David F., Zhang, Xiaohua, Glosli, James N., McCulloch, Andrew D., Krummen, David E., Lightstone, Felice C., and Wong, Sergio E. Fri . "Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study". United States. doi:10.1007/s13239-018-0347-0. https://www.osti.gov/servlets/purl/1463971.
@article{osti_1463971,
title = {Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study},
author = {Cranford, Jonathan P. and O’Hara, Thomas J. and Villongco, Christopher T. and Hafez, Omar M. and Blake, Robert C. and Loscalzo, Joseph and Fattebert, Jean-Luc and Richards, David F. and Zhang, Xiaohua and Glosli, James N. and McCulloch, Andrew D. and Krummen, David E. and Lightstone, Felice C. and Wong, Sergio E.},
abstractNote = {Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored. Thus, this study aimed to determine the sensitivity of the QRS complex of the ECG to the anatomical location and regional number of PMJs. The QRS complex was simulated using an image-based human torso and biventricular model, and cardiac electrophysiology was simulated using Cardioid. The PMJs were modeled as discrete current injection stimuli, and the location and number of stimuli were varied within initial activation regions based on published experiments. Results indicate that the QRS complex features were most sensitive to the presence or absence of four “seed” stimuli, and adjusting locations of nearby “regional” stimuli provided finer tuning. Decreasing number of regional stimuli by an order of magnitude resulted in virtually no change in the QRS complex. Thus, a minimal 12-stimuli configuration was identified that resulted in physiological excitation, defined by QRS complex feature metrics and ventricular excitation pattern. In conclusion, overall, the sensitivity results suggest that parameterizing PMJ location, rather than number, be given significantly higher priority in future studies creating personalized ventricular models from patient-derived ECGs.},
doi = {10.1007/s13239-018-0347-0},
journal = {Cardiovascular Engineering and Technology},
number = 3,
volume = 9,
place = {United States},
year = {2018},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share:

Works referenced in this record:

Contrast Enhanced Micro-Computed Tomography Resolves the 3-Dimensional Morphology of the Cardiac Conduction System in Mammalian Hearts
journal, April 2012


Alternans and spiral breakup in a human ventricular tissue model
journal, September 2006

  • ten Tusscher, K. H. W. J.; Panfilov, A. V.
  • American Journal of Physiology-Heart and Circulatory Physiology, Vol. 291, Issue 3
  • DOI: 10.1152/ajpheart.00109.2006

Patient-specific modeling of dyssynchronous heart failure: A case study
journal, October 2011

  • Aguado-Sierra, Jazmin; Krishnamurthy, Adarsh; Villongco, Christopher
  • Progress in Biophysics and Molecular Biology, Vol. 107, Issue 1
  • DOI: 10.1016/j.pbiomolbio.2011.06.014

Patient-specific models of cardiac biomechanics
journal, July 2013

  • Krishnamurthy, Adarsh; Villongco, Christopher T.; Chuang, Joyce
  • Journal of Computational Physics, Vol. 244
  • DOI: 10.1016/j.jcp.2012.09.015

Towards predictive modelling of the electrophysiology of the heart: Predictive modelling of cardiac electrophysiology
journal, April 2009


Current progress in patient-specific modeling
journal, December 2009

  • Neal, M. L.; Kerckhoffs, R.
  • Briefings in Bioinformatics, Vol. 11, Issue 1
  • DOI: 10.1093/bib/bbp049

Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function
journal, February 2010

  • Bishop, Martin J.; Plank, Gernot; Burton, Rebecca A. B.
  • American Journal of Physiology-Heart and Circulatory Physiology, Vol. 298, Issue 2
  • DOI: 10.1152/ajpheart.00606.2009

The Role of Purkinje-Myocardial Coupling during Ventricular Arrhythmia: A Modeling Study
journal, February 2014


Rapid Ventricular Tachycardia Due to His-Purkinje Reentry
journal, July 1984


Spiral-wave dynamics in a mathematical model of human ventricular tissue with myocytes and Purkinje fibers
journal, February 2017


Purkinje-Muscle Reentry as a Mechanism of Polymorphic Ventricular Arrhythmias in a 3-Dimensional Model of the Ventricles
journal, June 1998


An effective algorithm for the generation of patient-specific Purkinje networks in computational electrocardiology
journal, February 2015

  • Palamara, Simone; Vergara, Christian; Faggiano, Elena
  • Journal of Computational Physics, Vol. 283
  • DOI: 10.1016/j.jcp.2014.11.043

Modelling of the ventricular conduction system
journal, January 2008


Total Excitation of the Isolated Human Heart
journal, June 1970


A Novel Rule-Based Algorithm for Assigning Myocardial Fiber Orientation to Computational Heart Models
journal, May 2012


High resolution 3-Dimensional imaging of the human cardiac conduction system from microanatomy to mathematical modeling
journal, August 2017


Human ventricular activation sequence and the simulation of the electrocardiographic QRS complex and its variability in healthy and intraventricular block conditions
journal, December 2016

  • Cardone-Noott, Louie; Bueno-Orovio, Alfonso; Mincholé, Ana
  • EP Europace, Vol. 18, Issue suppl_4
  • DOI: 10.1093/europace/euw346

Generating Purkinje networks in the human heart
journal, August 2016


Towards real-time simulation of cardiac electrophysiology in a human heart at high resolution
journal, July 2013

  • Richards, David F.; Glosli, James N.; Draeger, Erik W.
  • Computer Methods in Biomechanics and Biomedical Engineering, Vol. 16, Issue 7
  • DOI: 10.1080/10255842.2013.795556

Whole-Heart Modeling: Applications to Cardiac Electrophysiology and Electromechanics
journal, January 2011


Image-Based Structural Modeling of the Cardiac Purkinje Network
journal, January 2015

  • Liu, Benjamin R.; Cherry, Elizabeth M.
  • BioMed Research International, Vol. 2015
  • DOI: 10.1155/2015/621034

Rabbit-specific ventricular model of cardiac electrophysiological function including specialized conduction system
journal, October 2011


Patient-specific generation of the Purkinje network driven by clinical measurements of a normal propagation
journal, August 2014

  • Vergara, Christian; Palamara, Simone; Catanzariti, Domenico
  • Medical & Biological Engineering & Computing, Vol. 52, Issue 10
  • DOI: 10.1007/s11517-014-1183-5

Patient-specific modelling of cardiac electrophysiology in heart-failure patients
journal, October 2014


A Real-Time QRS Detection Algorithm
journal, March 1985

  • Pan, Jiapu; Tompkins, Willis J.
  • IEEE Transactions on Biomedical Engineering, Vol. BME-32, Issue 3
  • DOI: 10.1109/TBME.1985.325532