Purpose of Study Ventricular noncompaction (VN) is a cardiomyopathy thought to result from an arrest of myocardial development at an early embryonic stage. When VN is associated with congenital heart disease, abnormal coronary arteries or defects that compromise myocardial perfusion through the coronary arteries may be seen. While the most apparent phenotypic features in the heart are the prominent trabeculations and deep intertrabecular recesses in the left ventricular apex, presumably, the primary abnormality affecting ventricular function is in the ventricular myocardium. We used three-dimensional echocardiography (3DE) to test the hypothesis that VN is a phenotypic finding that is present when myocardial perfusion from the coronary arteries is absent or diminished. If so, an increased endocardial surface area as seen in VN would favor perfusion of the myocardium from the ventricular cavity.
Methods Used We studied the hearts of patients with clinical VN or patients with a family history of VN as well as the classic echocardiographic features of VN. These hearts were compared with hearts from age-matched "normal " patients. We used 3DE to orient the heart in a standard 4-chamber view and to allow the study of the entire left ventricle using serial planar sections through the chamber. We used a Phillips ie33 3DE machine to perform the echocardiograms and measured the left ventricular size, mass, volumes, and ejection fraction using the Q-lab software package. We subsequently analyzed serial sections of the left ventricle using standard morphometric techniques to measure the endocardial surface area and surface to volume ratio in the left ventricle.
Summary of Results/Conclusions 3DE can be used to characterize and analyze the morphology of the left ventricular myocardium in patients with VN. Measurements of surface area and surface to volume ratio in the affected myocardium may prove to be useful in studying the correlation between diminished coronary flow and the myocardial abnormalities observed in VN. These data may be useful in ultimately predicting the clinical course and following the progression of VN.
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