Author + information
- Received October 22, 2018
- Revision received December 10, 2018
- Accepted December 10, 2018
- Published online June 12, 2019.
- Christopher M. Bianco, DO,
- Peter D. Farjo, MD,
- Yasir A. Ghaffar, MD and
- Partho P. Sengupta, MD, DM∗ (, )@ppsengupta1
- Division of Cardiology, West Virginia University Heart and Vascular Institute, Morgantown, West VirginiaDivision of Cardiology, West Virginia University Heart and Vascular Institute, Morgantown, West Virginia
- ↵∗Address for correspondence:
Dr. Partho P. Sengupta, West Virginia University Heart and Vascular Institute, 1 Medical Center Drive, Morgantown, West Virginia 26506-8059.
• HFpEF is a complex clinical entity that is poorly understood yet is present in up to 5.5% of the general population.
• Assessment of myocardial mechanics provides unique insight into the pattern of the myocardial dysfunction observed during disease progression through preclinical and clinical HFpEF.
• Novel phenotyping methods, including machine learning, can integrate these myocardial mechanics into clinical groups used to advise and treat patients.
Heart failure with preserved ejection fraction (HFpEF) is a complex clinical entity that is poorly understood yet present in up to 5.5% of the general population. Proven therapies for this disorder are lacking, even though it has a similar prognosis to that of heart failure with reduced ejection fraction (HFrEF). Innovative imaging techniques have provided in-depth understanding of the unique pattern of left ventricular mechanics in patients with HFpEF who progress through preclinical (Stages A to B) and clinical (Stages C to D) American College of Cardiology/American Heart Association heart failure stages. This review highlights the mechanical basis of this disorder from the cellular and myofiber level to chamber dysfunction. As each chamber of the heart is examined, specific biomarkers and echocardiographic parameters with diagnostic and prognostic values are discussed. Finally, novel phenotyping methods including machine learning are reviewed that integrate these mechanics into clinical groups to advise and treat patients.
- deformation imaging
- diastolic dysfunction
- global longitudinal strain
- heart failure with preserved ejection fraction
- left atrial strain
- left ventricular strain
- myocardial strain
- right ventricular strain
Dr. Bianco is a private investigator for an AstraZeneca trial. Dr. Sengupta is an advisor to HeartSciences, Ultromics, and Hitachi Ltd. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Sherif Nagueh, MD, served as Guest Editor for this paper.
- Received October 22, 2018.
- Revision received December 10, 2018.
- Accepted December 10, 2018.
- 2019 American College of Cardiology Foundation
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