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Research Papers

Bridging Organ- and Cellular-Level Behavior in Ex Vivo Experimental Platforms Using Populations of Models of Cardiac Electrophysiology

[+] Author and Article Information
Carlos A. Ledezma, P. J. Tan

Department of Mechanical Engineering,
University College London,
London WC1E7JE, UK

Benjamin Kappler, Marco Stijnen

LifeTec Group,
Eindhoven 5611 ZS, The Netherlands

Veronique Meijborg, Bas Boukens

Department of Medical Biology,
Amsterdam UMC,
Amsterdam 1105 AZ, The Netherlands

Vanessa Díaz-Zuccarini

Department of Mechanical Engineering,
University College London,
London WC1E7JE, UK
e-mail: v.diaz@ucl.ac.uk

1Corresponding author.

Manuscript received May 16, 2018; final manuscript received June 11, 2018; published online July 24, 2018. Editor: Ahmed Al-Jumaily.

ASME J of Medical Diagnostics 1(4), 041003 (Jul 24, 2018) (7 pages) Paper No: JESMDT-18-1023; doi: 10.1115/1.4040589 History: Received May 16, 2018; Revised June 11, 2018

The inability to discern between pathology and physiological variability is a key issue in cardiac electrophysiology since this prevents the use of minimally invasive acquisitions to predict early pathological behavior. The goal of this work is to demonstrate how experimentally calibrated populations of models (ePoM) may be employed to inform which cellular-level pathologies are responsible for abnormalities observed in organ-level acquisitions while accounting for intersubject variability; this will be done through an exemplary computational and experimental approach. Unipolar epicardial electrograms (EGM) were acquired during an ex vivo porcine heart experiment. A population of the Ten Tusscher 2006 model was calibrated to activation–recovery intervals (ARI), measured from the electrograms, at three representative times. The distributions of the parameters from the resulting calibrated populations were compared to reveal statistically significant pathological variations. Activation–recovery interval reduction was observed in the experiments, and the comparison of the calibrated populations of models suggested a reduced L-type calcium conductance and a high extra-cellular potassium concentration as the most probable causes for the abnormal electrograms. This behavior was consistent with a reduction in the cardiac output (CO) and was confirmed by other experimental measurements. A proof of concept method to infer cellular pathologies by means of organ-level acquisitions is presented, allowing for an earlier detection of pathology than would be possible with current methods. This novel method that uses mathematical models as a tool for formulating hypotheses regarding the cellular causes of observed organ-level behaviors, while accounting for physiological variability has been unexplored.

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Figures

Grahic Jump Location
Fig. 2

Example of experimental calibration. The figure shows the full population of TP06 models and, highlighted, the ePoM corresponding to ARIs in the range [220,250] ms.

Grahic Jump Location
Fig. 1

Example of ARI measurement. The image shows a typical beat (positive deflection), its derivative (negative deflection, scaled for clarity), its activation time (vertical line on the left), and recovery time (vertical line on the right).

Grahic Jump Location
Fig. 3

Flowchart summarizing the proposed methodology. Here, N = 15,000 samples to be taken using LHS, K = 3 time points at which the experimental acquisitions were made and C = 121 electrodes in the grid.

Grahic Jump Location
Fig. 4

Histograms showing the distribution of ARIs at the three time points of the experiment: (a) time point 1, (b) time point 2, and (c) time point 3

Grahic Jump Location
Fig. 5

Experimentally calibrated populations of models parameter distributions for a representative channel (channel 6) at the three time points. Horizontal dashed lines are the standard values of the parameters from the original TP06 model [14]. Gx are in nS/pF and Pnak and knaca are in pA/pF.

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