I lead the Cardiac Systems Simulation (CardSS) Lab in the Bioengineering department at the University of Washington (UW). Our lab uses computer models of the heart to cultivate new knowledge about heart rhythm disorders. We use MRI scans from individual patients to power these complex “virtual heart” simulations. We use these powerful tools to discover underlying causes of disease or devise new treatment strategies that deliver better patient outcomes. An illustrative video based on my previous research can be viewed via this link.
The Cardiac Systems Simulation (CardSS) Lab uses models of the human heart to cultivate knowledge about arrhythmia mechanisms and concoct new treatment strategies for these conditions. These problems are part of an enormous global health concern, especially since heart rhythm disorders are becoming more prevalent as the number of elderly individuals continues to grow. We are developing approaches to identify those with future risk of complications (sudden cardiac arrest, embolic stroke of undetermined source, worsening arrhythmia) via simulations in models reconstructed from MRI scans. We are also using computational tools to lower barriers to translation in regenerative medicine via injection of heart-like cells derived from a patient’s own stem cells. The same modeling techniques can help us envision and text radical new biomedical devices like light-based defibrillators. Our most recent research thrust uses artificial intelligence and machine learning to tease information out of standard EKG signals. This is particularly noteworthy in the context of COVID-19, since we can help front-line care teams predict risk for heart complications while reducing the need for daily measurements. Finally, we have an overarching interest in driving technological development to accelerate and simplify the cardiac modeling process.
Our work is highly interdisciplinary and often involves frequent and intense interaction with collaborators including high performance computing experts, wet lab biologists, optics researchers, medical imaging specialists, and cardiologists conducting procedures to treat arrhythmia in patients. Our trainees are deeply embedded in translational research and attend weekly clinical meetings with the full UW Medicine cardiac electrophysiology team, where they are exposed to the same high-level content learned by fellows-in-training.
Boyle PM*, Franceschi WH*, et al. New insights on the cardiac safety factor: Unraveling the relationship between conduction velocity and robustness of propagation. J Mol Cell Cardiol. 2019 Mar;128:117-128. PMID: 30677394.
Boyle PM, et al. Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation. Front Physiol. 2018 Apr 19;9:414. PMID: 29725307
Boyle PM, et al. Termination of re-entrant atrial tachycardia via optogenetic stimulation with optimized spatial targeting: insights from computational models. J Physiol. 2018 Jan 15;596(2):181-196. PMID: 29193078
Deng D*, Murphy MJ*, […], and Boyle PM. Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate. Chaos. 2017 Sep;27(9):093932. PMID: 28964164
Bruegmann T*, Boyle PM*, et al. Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations. J Clin Invest. 2016 Oct 3;126(10):3894-3904. PMID: 27617859
Zahid S*, Cochet H*, Boyle PM*, et al. Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern. Cardiovasc Res. 2016 Jun 1;110(3):443-54. PMID: 27056895
Boyle PM*, Park CJ*, et al. Sodium current reduction unmasks a structure-dependent substrate for arrhythmogenesis in the normal ventricles. PLoS One. 2014 Jan 28;9(1):e86947. PMID: 24489810
Boyle PM et al. A comprehensive multiscale framework for simulating optogenetics in the heart. Nat Commun. 2013;4:2370. PMID: 23982300
Boyle PM et al. Transmural IK(ATP) heterogeneity as a determinant of activation rate gradient during early ventricular fibrillation: mechanistic insights from rabbit ventricular models. Heart Rhythm. 2013 Nov;10(11):1710-7. PMID: 23948344
Boyle PM et al. Fusion during entrainment of orthodromic reciprocating tachycardia is enhanced for basal pacing sites but diminished when pacing near Purkinje system end points. Heart Rhythm. 2013 Mar;10(3):444-51. PMID: 23207137
Boyle PM and Vigmond EJ. An intuitive safety factor for cardiac propagation. Biophys J. 2010 Jun 16;98(12):L57-9. PMID: 20550885
Boyle PM et al. Purkinje-mediated effects in the response of quiescent ventricles to defibrillation shocks. Ann Biomed Eng. 2010 Feb;38(2):456-68. PMID: 19876737