Literature DB >> 7790012

Predicting cardiothoracic voltages during high energy shocks: methodology and comparison of experimental to finite element model data.

D B Jorgenson1, P H Schimpf, I Shen, G Johnson, G H Bardy, D R Haynor, Y Kim.   

Abstract

Finite element modeling has been used as a method to investigate the voltage distribution within the thorax during high energy shocks. However, there have been few quantitative methods developed to assess how well the calculations derived from the models correspond to measured voltages. In this paper, we present a methodology for recording thoracic voltages and the results of comparisons of these voltages to those predicted by finite element models. We constructed detailed 3-D subject-specific thorax models of six pigs based on their individual CT images. The models were correlated with the results of experiments conducted on the animals to measure the voltage distribution in the thorax at 52 locations during synchronized high energy shocks. One transthoracic and two transvenous electrode configurations were used in the study. The measured voltage values were compared to the model predictions resulting in a correlation coefficient of 0.927 +/- 0.036 (average +/- standard deviation) and a relative rms error of 22.13 +/- 5.99%. The model predictions of voltage gradient within the myocardium were also examined revealing differences in the percent of the myocardium above a threshold value for various electrode configurations and variability between individual animals. This variability reinforces the potential benefit of patient-specific modeling.

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Year:  1995        PMID: 7790012     DOI: 10.1109/10.387195

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  8 in total

1.  Validating defibrillation simulation in a human-shaped phantom.

Authors:  Jess D Tate; Thomas A Pilcher; Kedar K Aras; Brett M Burton; Rob S MacLeod
Journal:  Heart Rhythm       Date:  2019-11-23       Impact factor: 6.343

2.  Experience with unipolar pectoral defibrillation.

Authors:  R K Reddy; G H Bardy
Journal:  Herzschrittmacherther Elektrophysiol       Date:  1997-03

3.  Measuring defibrillator surface potentials: The validation of a predictive defibrillation computer model.

Authors:  Jess Tate; Jeroen Stinstra; Thomas Pilcher; Ahrash Poursaid; Matthew A Jolley; Elizabeth Saarel; John Triedman; Rob S MacLeod
Journal:  Comput Biol Med       Date:  2018-08-29       Impact factor: 4.589

4.  Effects of electrode interface impedance on finite element models of transvenous defibrillation.

Authors:  P H Schimpf; G Johnson; D B Jorgenson; D R Haynor; G H Bardy; Y Kim
Journal:  Med Biol Eng Comput       Date:  1995-09       Impact factor: 2.602

5.  A toolkit for forward/inverse problems in electrocardiography within the SCIRun problem solving environment.

Authors:  Brett M Burton; Jess D Tate; Burak Erem; Darrell J Swenson; Dafang F Wang; Michael Steffen; Dana H Brooks; Peter M van Dam; Rob S Macleod
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

6.  Predictive modeling of defibrillation using hexahedral and tetrahedral finite element models: recent advances.

Authors:  John K Triedman; Matthew Jolley; Jeroen Stinstra; Dana H Brooks; Rob MacLeod
Journal:  J Electrocardiol       Date:  2008-09-24       Impact factor: 1.438

7.  A computer modeling tool for comparing novel ICD electrode orientations in children and adults.

Authors:  Matthew Jolley; Jeroen Stinstra; Steve Pieper; Rob Macleod; Dana H Brooks; Frank Cecchin; John K Triedman
Journal:  Heart Rhythm       Date:  2008-01-17       Impact factor: 6.343

Review 8.  Remote and wearable ECG devices with diagnostic abilities in adults: A state-of-the-science scoping review.

Authors:  Zeineb Bouzid; Salah S Al-Zaiti; Raymond Bond; Ervin Sejdić
Journal:  Heart Rhythm       Date:  2022-03-09       Impact factor: 6.779

  8 in total

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