Journal of Exercise Science & Fitness (Dec 2014)
Diastolic function alteration mechanisms in physiologic hypertrophy versus pathologic hypertrophy are elucidated by model-based Doppler E-wave analysis
Abstract
Athletic training can result in increased left ventricular (LV) wall thickness, termed physiologic hypertrophy (PhH). By contrast, pathologic hypertrophy (PaH) can be due to hypertension, aortic stenosis, or genetic mutation causing hypertrophic cardiomyopathy (HCM). Because morphologic (LV dimension, wall thickness, mass, etc.) and functional index similarities (LV ejection fraction, cardiac output, peak filling rate, etc.) limit diagnostic specificity, ability to differentiate between PhH and PaH is important. Conventional echocardiographic diastolic function (DF) indexes have limited ability to differentiate between PhH and PaH and cannot provide information on chamber property (stiffness and relaxation). We hypothesized that kinematic model-based DF assessment can differentiate between PhH and PaH and, by providing chamber properties, has even greater value compared with conventional metrics. For validation, we assessed DF in the following three age-matched groups: pathologic (HCM) hypertrophy (PaH, n = 14), PhH (Olympic rowers, PhH, n = 21), and controls (n = 21). Magnetic resonance imaging confirmed presence of both types of hypertrophy and determined LV mass and chamber size. Model-based indexes, chamber stiffness (k), relaxation/viscoelasticity (c), and load (xo) and conventional indexes, Epeak (peak of E-wave), ratio of Epeak to Apeak (E/A), E-wave acceleration time (AT), and E-wave deceleration time (DT) were computed. We analyzed 1588 E waves distributed as follows: 328 (PaH), 672 (athletes), and 588 (controls). Among conventional indexes, Epeak and E-wave DT were similar between PaH and PhH, whereas E/A and E-wave AT were lower in PaH. Model-based analysis showed that PaH had significantly higher relaxation/viscoelasticity (c) and chamber stiffness (k) than PhH. The physiologic equation of motion for filling-based derivation of the model provides a mechanistic understanding of the differences between PhH and PaH.
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