Clinical validation of an automated boundary tracking algorithm on cardiac MR images

The goal of this research was to develop an automated algorithm for tracking the borders of the left ventricle (LV) in a cine-MRI gradient-echo temporal data set. The algorithm was validated on four patient populations: healthy volunteers and patients with dilated cardiomyopathy (DCM), left ventricular hypertrophy (LVH), or left ventricular aneurysm (LVA). A full tomographic set (approximately 11 slices/case) of short-axis images through systole was obtained for each patient. Initial endocardial and epicardial contours for the end-diastolic (ED) and end-systolic (ES) frames were manually traced on the computer by an experienced radiologist. The ED tracings were used as the starting point for the algorithm. The borders were tracked through each phase of the temporal data set, until the ES frame was reached (approximately 7 phases/slice). Peak gradients along equally spaced chords calculated perpendicular to a centerline determined midway between the endocardial and epicardial borders were used for border detection. This approach was tested by comparing the LV epicardial and endocardial volumes calculated at ES to those based on the manual tracings. The results of the algorithm compared favorably with both the endocardial (r2 = 0.72 - 0.98) and epicardial (r2 = 0.96 - 0.99) volumes of the tracer.