Appointments and affiliations
Interventional Cardiologist and Clinician-Scientist
University of Ottawa Heart Institute
Assistant Professor
University of Ottawa
Chief Technology Officer and Co-Founder
Tomoverse Imaging Inc.
Dr. Pascal Thériault-Lauzier is a clinician-scientist and cardiologist specializing in structural interventions at the University of Ottawa Heart Institute. He also holds an appointment as assistant professor in the Faculty of Medicine at the University of Ottawa.
Background
Dr. Thériault-Lauzier earned a Bachelor of Science with first-class honours in physics from McGill University in 2008. He completed a Master of Science (2010) and a Doctor of Philosophy degree (2012) in medical physics at the University of Wisconsin-Madison, where his research focused on advanced imaging reconstruction techniques in cardiac computed tomography (CT). Dr. Thériault-Lauzier earned his medical degree from McGill University in 2016. He completed residencies in internal medicine (2019) at McGill University and in adult cardiology (2022) at the University of Ottawa Heart Institute. He subsequently completed fellowships in interventional cardiology and structural heart interventions at the Heart Institute and Stanford University. He also completed a research fellowship in artificial intelligence at the Montréal Heart Institute.
Research and clinical interests
Dr. Thériault-Lauzier’s clinical expertise includes percutaneous coronary interventions, transcatheter aortic valve replacement (TAVR), left atrial appendage occlusion, and edge-to-edge mitral and tricuspid valve repair. He is also involved in emerging therapies, such as transcatheter mitral and tricuspid valve replacement. His clinical practice emphasizes the use of innovative procedural techniques to optimize patient outcomes.
Dr. Thériault-Lauzier’s research focuses on the integration of advanced computational methods into cardiac imaging and interventions. He leads projects aimed at automating cardiac image analysis, enhancing procedural planning, and improving diagnostic accuracy. His research portfolio includes the development of AI algorithms for applications such as automated CT image analysis for TAVR planning, synthetic angiography, and predicting hemodynamic parameters from coronary angiography. He is interested in translating AI advancements into clinical practice through multidisciplinary collaborations and rigorous clinical validation.