Person:

Hiremath, Pranoti

The transition from healthy myocardium to hypertensive heart disease is characterized by a series of poorly understood changes in myocardial tissue microstructure. Incremental alterations in the orientation and integrity of myocardial fibers can be assessed using advanced ultrasonic image analysis. We used a modified algorithm to investigate left ventricular myocardial microstructure based on analysis of the reflection intensity at the myocardial-pericardial interface on B-mode echocardiographic images. We evaluated the extent to which the novel algorithm can differentiate between normal myocardium and hypertensive heart disease in humans as well as in a mouse model of afterload resistance. The algorithm significantly differentiated between individuals with uncomplicated essential hypertension (N = 30) and healthy controls (N = 28), even after adjusting for age and sex (P = 0.025). There was a trend in higher relative wall thickness in hypertensive individuals compared to controls (P = 0.08), but no difference between groups in left ventricular mass (P = 0.98) or total wall thickness (P = 0.37). In mice, algorithm measurements (P = 0.026) compared with left ventricular mass (P = 0.053) more clearly differentiated between animal groups that underwent fixed aortic banding, temporary aortic banding, or sham procedure, on echocardiography at 7 weeks after surgery. Based on sonographic signal intensity analysis, a novel imaging algorithm provides an accessible, non-invasive measure that appears to differentiate normal left ventricular microstructure from myocardium exposed to chronic afterload stress. The algorithm may represent a particularly sensitive measure of the myocardial changes that occur early in the course of disease progression.

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.