Identifying Changes in Myocardial Microstructure via a Novel Sonographic Imaging Algorithm

Abstract

We developed a novel ultrasound-based image analysis algorithm designed to differentiate microstructural characteristics of left ventricular (LV) myocardium. The algorithm analyzes sonographic signal distributions and produces a marker termed the signal intensity coefficient (SIC), which can serve as an enhanced surrogate measure of myocardial microstructure. We evaluated our algorithm in two disease processes that are characterized by progressive LV remodeling from microstructural to global myocardial changes: hypertensive heart disease and hypertrophic cardiomyopathy. Results demonstrate that the SIC was significantly higher in hypertensive compared to non-hypertensive myocardium in both mice and humans, and was positively associated with increasing levels of exposure to afterload stress in humans and mice. Furthermore, in a cohort of sarcomere mutation carriers with different phenotypes of HCM, the SIC was able to distinguish between individuals with overt HCM, subclinical HCM, and healthy controls. The SIC demonstrated stronger associations with both degree of blood pressure and MRI-based ECV compared to established echocardiographic measures of adverse LV remodeling. Overall, our results demonstrate the potential of an imaging algorithm to identify the presence and extent of microstructural changes that can arise early in development of cardiac remodeling, in response to chronic exposure to afterload stress as well as genetic mutations.