Feasibility of identifying amyloid and hypertrophic cardiomyopathy with the use of computerized quantitative texture analysis of clinical echocardiographic data

Ultrasound tissue characterization, the evaluation of certain physical properties of a tissue based on its acoustic properties, is an evolving application in echocardiography. The ability to identify acutely and chronically injured tissue has been demonstrated in a number of animal studies, but data in humans are limited. The present study tested the hypothesis that quantitative echocardiographic texture analysis, a method of evaluating the spatial pattern of echoes in echocardiographic images, would differentiate amyloid and hypertrophic cardiomyopathy from normal myocardium. Routine clinical echocardiographic data were obtained on 34 subjects at the Mayo Clinic (10 normal subjects, 10 patients with amyloid heart disease, 8 patients with hypertrophic cardiomyopathy and 6 patients with left ventricular hypertrophy due to hypertension). Standard videotape recordings of these echocardiograms were analyzed at the University of Iowa. Echocardiographic data were digitized with use of a calibrated, 256 gray level digitization system. Quantitative texture analysis was performed on data from the ventricular septum and posterior left ventricular wall in end-diastolic and end-systolic, short-axis and long-axis echocardiographic images. The gray level run length texture variables were able to discriminate hypertrophic cardiomyopathy and amyloid heart disease from normal myocardium and from each other (p < 0.0083 for comparisons of the quantitative texture features of amyloid versus hypertrophic cardiomyopathy versus normal by multivariate analysis of variance). The texture of the myocardium in hypertensive left ventricular hypertrophy not associated with amyloid or hypertrophic cardiomyopathy was in general not significantly different from that of normal myocardium. On the basis of these data, it was concluded that quantitative texture analysis of clinical echocardiographic data has the potential to identify amyloid and hypertrophic cardiomyopathy; false positive results occur rarely in left ventricular hypertrophy due to hypertension. Further prospective studies of this technique are needed to establish its utility in identifying the etiology of clinical cardiomyopathies.