Kenneth Bilchick, MD, MS
Professor of Cardiovascular Medicine, University of Virginia
Director of Electrophysiology Research, University of Virginia
Member Institutional Review Board for Human Subjects Research, University of Virginia
Medical Director, EP Device Clinic, University of Virginia
Medical Director, Heart Rhythm QST, University of Virginia
Member, External Funding & Research Administration Working Group, University of Virginia
Member, Cardiovascular Imaging Center
Chair (Incoming), Heart Rhythm Society Research Committee
Chair, Society for Cardiovascular Magnetic Resonance Research Committee
Member, ACC/NCDR Research and Publications Committee
Ad Hoc Reviewer for NIH Study Sections
Member, Executive Committee for the PCORI-funded Left versus Left Randomized Clinical Trial
Recent work has highlighted applications of cardiac magnetic resonance (CMR) for patients with heart rhythm disorders and heart failure, including studies with collaborators across the United States. With his expertise as a statistician, he is investigating machine learning applications to CMR and electrocardiographic data in patients with cardiac implantable electronic devices. His research employs advanced cardiac imaging, image integration with 3D invasive electroanatomic mapping, and electrocardiographic waveform analysis/signal processing to improve electrophysiology procedures such as cardiac resynchronization therapy (CRT), left bundle branch pacing, and catheter ablation for atrial fibrillation and ventricular tachycardia. He is also engaged in clinical studies of flow cytometry by time of flight (CyTOF) and anti-inflammatory therapies for heart failure, and studies of therapeutic approaches and AI in hypertrophic cardiomyopathy; other areas of interest are longitudinal data analysis in heart failure and analysis of administrative datasets/registries to identify predictors of clinical benefit with implantable cardioverter defibrillators.
HIGH IMPACT RESEARCH PUBLICATIONS
- Machine learning for multidimensional response and survival after cardiac resynchronization therapy using features from cardiac magnetic resonance.
- Bivona DJ, Tallavajhala S, Abdi M, Oomen PJA, Gao X, Malhotra R, Darby AE, Monfredi OJ, Mangrum JM, Mason PK, Mazimba S, Salerno M, Kramer CM, Epstein FH, Holmes JW, Bilchick KC.Heart Rhythm O2. 2022 Jun 17;3(5):542-552. doi: 10.1016/j.hroo.2022.06.005. eCollection 2022 Oct.PMID: 36340495
- Survival Probability and Survival Benefit Associated With Primary Prevention Implantable Cardioverter-Defibrillator Generator Changes.
- Bilchick KC, Wang Y, Curtis JP, Shadman R, Dardas TF, Anand I, Lund LH, Dahlström U, Sartipy U, Levy WC.J Am Heart Assoc. 2022 Jul 5;11(13):e023743. doi: 10.1161/JAHA.121.023743. Epub 2022 Jun 29.PMID: 35766293
- Cardiac Magnetic Resonance Assessment of Response to Cardiac Resynchronization Therapy and Programming Strategies.
- Gao X, Abdi M, Auger DA, Sun C, Hanson CA, Robinson AA, Schumann C, Oomen PJ, Ratcliffe S, Malhotra R, Darby A, Monfredi OJ, Mangrum JM, Mason P, Mazimba S, Holmes JW, Kramer CM, Epstein FH, Salerno M, Bilchick KC.JACC Cardiovasc Imaging. 2021 Dec;14(12):2369-2383. doi: 10.1016/j.jcmg.2021.06.015. Epub 2021 Aug 18.PMID: 34419391
- CMR DENSE and the Seattle Heart Failure Model Inform Survival and Arrhythmia Risk After CRT.
- Bilchick KC, Auger DA, Abdishektaei M, Mathew R, Sohn MW, Cai X, Sun C, Narayan A, Malhotra R, Darby A, Mangrum JM, Mehta N, Ferguson J, Mazimba S, Mason PK, Kramer CM, Levy WC, Epstein FH.JACC Cardiovasc Imaging. 2020 Apr;13(4):924-936. doi: 10.1016/j.jcmg.2019.10.017. Epub 2019 Dec 18.PMID: 31864974
- Seattle Heart Failure and Proportional Risk Models Predict Benefit From Implantable Cardioverter-Defibrillators.
- Bilchick KC, Wang Y, Cheng A, Curtis JP, Dharmarajan K, Stukenborg GJ, Shadman R, Anand I, Lund LH, Dahlström U, Sartipy U, Maggioni A, Swedberg K, O’Conner C, Levy WC.J Am Coll Cardiol. 2017 May 30;69(21):2606-2618. doi: 10.1016/j.jacc.2017.03.568.PMID: 28545633