Jess Tate

Implantable Cardioverter Defibrillators (ICDs) are widely medical devices used to prevent death from fatal cardiac arrhythmias. The development of these devices is mature and they yield successful outcomes in many cases, yet the standard use of these devices is ineffective in many patients at high risk for fatal arrhythmias, especially children and individuals with abnormal cardiac anatomy or congenital heart defects[1]. Furthermore, the standard implantation and development of defibrillators is based on a notion of delivering more energy and shocks than needed to ensure defibrillation, so that in many instances the lowest energy needed for a given patient is not explored. It is probable that many seemingly successful treatments in the normal patient range are being shocked with more energy than needed, causing unnecessary damage and increasing the mortality of the patient[2].

As a result, there is a need for an individualized approach to implanting and developing defibrillators and the research group to which I belong has developed new simulation technology that enables users to predict the effect the defibrillators on isolated hearts and full torsos. Isolated biophysical heart models use the anatomy and fiber structure of individual hearts to simulate fibrillation and subsequently the effect of a defibrillation pulse on the fibrillating tissue[3]. This model incorporates the active properties of the myocardial tissue to evaluate the effectiveness of the shock in eliminating reentrant pathways, circulating currents that develop into fibrillation, and consequently defibrillating the heart. Current torso models incorporate many tissue types in the static evaluation of an induced electric field. The resulting electric field through the heart is used to calculate the energy required for defibrillation[4]. Each type of model contains intrinsic limitations due to the nature of the model.

A biophysical heart model developed at Johns Hopkins University and a static torso model developed at the University of Utah have provided preliminary evidence that each are robust models for defibrillation. The isolated heart model have shown consistent prediction of defibrillation treatment with what is observed clinically[3]. Preliminary studies comparing a patient’s energy threshold yielded a promising correlation between the predicted and actual values[4]. Other preliminary findings show a similar distribution pattern of the predicted surface potentials and measured values (see research experience). Though the preliminary findings of each of the models show promising potential in the prediction defibrillation, a combination of both types of simulation would allow for more detail and the evaluation and optimization of more parameters than either method is able to do independently.

• 1. Kugler J, CC E: Nontransvenous implantable cardioverter defibrillator systems: not just for small pediatric patients. J Cardiovasc Electrophysiol 2006, 17:47-48.
• 2. Ristagno G, Wang T, Tang W, Sun S, Castillo C, Weil MH: High-energy defibrillation impairs myocyte contractility and intracellular calcium dynamics. Critical Care Medicine 2008, 36(11):S422-S427.
• 3. Aguel F, Eason JC, Trayanova NA, Siekas G, Fishler MG: Impact of transvenous lead position on active-can ICD defibrillation: a computer simulation study. PACE 1999, 22:158.
• 4. Jolley M, Stinstra J, Pieper S, MacLeod R, Brooks DH, Cecchin F, Triedman JK: A Computer Modeling Tool for Comparing Novel ICD Electrode Orientations in Children and Adults. Heart Rhythm 2008, 5:565-572.

Our goal is to develop and validate a computational model of the heart and torso that can be used to quickly test new implantation strategies and device designs. We will achieve this goal by implementing an isolated biophysical heart model into a static torso model. We hypothesize that this new patient-specific model is able to provide unbiased and accurate evaluation of the defibrillation threshold based on the desired parameters. The three aims of this study that will lead to the realization of our goal and in which I will participate as part of my PhD research are: 1) develop a database of pediatric cardiac geometries and fiber structure for isolated heart biophysical defibrillation simulations, 2) incorporate the isolated heart simulations into static torso models, and 3) validate the defibrillation models in humans with surface recordings obtained during ICD implantation surgeries and testing.

This project will provide a rich environment for my doctoral research; it is a collaborative effort from three research centers: University of Utah, Johns Hopkins University, and Harvard Medical School. I will benefit from this rich environment and the outstanding local resources of the Scientific Computing and Imaging (SCI) Institute and Cardiovascular Research and Training Institute (CVRTI) as I carry out specific projects in the creation of patient specific geometric models and simulation of defibrillation.

I will develop a database of pediatric heart models by generating computational meshes of autopsied human hearts obtained from Children’s Hospital Boston and Harvard University under strict IRB protocols. I will oversee the scanning of these hearts using MRI (7 Telsa small animal scanner) and diffusion tensor imaging (DTI) to obtain the anatomy and fiber structure that will form the basis of the models. I will then generate the meshes and map the fibers for inclusion in the database using the open-source software tools Seg3D and SCIRun developed at the SCI Institute.

With collaboration with Dr. Natalia Trayanova from the Biomedical Engineering Department at Johns Hopkins University, I will integrate the isolated heart models and the static torso models for a state of the art defibrillation model. I will carry out simulations of defibrillation using SCIRun (the torso component) and interface with the simulations generated by Dr. Trayanova’s group from the aforementioned pediatric heart database (the cardiac component).

Validation of the model in humans will consist of obtaining body surface recordings from pediatric patients in whom ICDs have been implanted. The process will begin with detailed MRI scans of the subjects under an existing IRB protocol at the University of Utah Primary Children’s Hospital. I will oversee scanning and then segment and create geometric models from the images using similar approaches as with the cardiac models. During the testing phase of the ICD implantation procedure, I will record body surface potentials using a custom made acquisition system we have developed at the CVRTI. Fluoroscopy images from the patient after the implantation will provide ICD location information, which will determine placement of the device in the computer model. Comparison of the measured and simulated torso surface potentials will provide validation information and guide subsequent modification of the model.

Success in this biomedical engineering project will result in an overall improvement of the use and the design of future defibrillation devices. Doctors and engineers will be able to test ideas and configurations before conducting expensive and invasive trials. While the fast and simple test method provided by this model will improve all patient care by allowing technology developers to design more optimal ICDs, it will have special impact in ICD use in children. Completing this project will assuredly lead to new pediatric driven devices. Even before new ICDs are released, better placement of the device can lower thresholds, reducing patient discomfort, increasing battery lifetimes and reduce the frequency of replacement surgeries, significantly reducing the major complications associated with using ICD for pediatric cases.