Patrick M. Boyle

Assistant Professor
Phone: (206) 685-1392
Office: Foege N310H (main campus); Brotman 311 (SLU)

Outline of computational and mathematical framework for multi-scale simulations of cardiac electrophysiology

Patrick M. Boyle

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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.

  1. Predicting future health risks in patients with embolic stroke of undetermined source
  2. Optimizing treatment of atrial rhythm disorders via personalized simulations
  3. Conceptualizing next-gen cardiac devices that harness new tech like optogenetics
  4. Investigating new applications of heart-like cells induced from patient-derived stem cells
  5. Exploiting AI to predict lethal cardiovascular events, including in patients with COVID-19

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.

Ph.D., Biomedical Engineering, University of Calgary, 2011

B.Sc. with Distinction, Internship program, Computer Engineering, University of Calgary, 2005 

Assistant Research Professor, Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, 2015-18

Assistant Research Scientist, Institute for Computational Medicine, Johns Hopkins University, 2014-15

NSERC Postdoctoral Fellow, Computational Cardiology Lab, Institute for Computational Medicine, Johns Hopkins University, 2011-14

UW Population Health Initiative, COVID-19 Rapid Response Grant, 2020

American Heart Association Scientist Development Grant, 2016-19

Appointed as a Fellow of the Heart Rhythm Society (FHRS designation), 2017

Special Selection: Heart Rhythm Society EP Concepts Ignited Session, 2017

Licensed as a Canadian Professional Engineer (P.Eng. designation), 2013

Cardiac Physiome Workshop, Outstanding Scientific Poster Presentation, 2012

Computing in Cardiology Conference, Rosanna Degani Young Investigator Award (Finalist), 2012

NSERC Post-Doctoral Fellowship, 2011-13

AStech Foundation Leaders of Tomorrow (Honouree), 2011

NSERC Post-Graduate Scholarship D, 2008-10

NSERC Post-Graduate Scholarship M, 2005-07

BIOEN400: Fundamentals of Bioengineering Design [link]

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* Equal co-author contributions

Boyle PM*, Zghaib T*, et al. Computationally guided personalized targeted ablation of persistent atrial fibrillation. Nat Biomed Eng. 2019 Nov;3(11):870-879. PMID: 31427780.

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, Karathanos TV, Trayanova NA. Cardiac Optogenetics: 2018 (Invited State-of-the-art Review). JACC Clin Electrophysiol. 2018 Feb;4(2):155-167. PMID: 29749932

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

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