Automated Assessment of Ventricular Volume and Function by Echocardiography: Validation of Automated Border Detection

To determine the utility of a new on-line echocardiography automated border detection (ABD) algorithm in assessing ventricular volume and ejection fraction, an optimal model was studied. This open-chest canine model allowed continuous measurement of actual left ventricular volume. In four dogs, true end-systolic and end-diastolic volume and ejection fraction were compared with those obtained by two-dimensional echocardiography with an automated method calculated from a border detection algorithm to define left ventricular endocardium and the single-plane Simpson method to calculate volume. Left ventricular volumes that used manual, off-line tracings of the left ventricle by two-dimensional echocardiograms and the single-plane Simpson method were compared. The automated echocardiography volumes correlated with true volumes ( y = 0.7 x + 8.9; standard error of the estimate=13.5 cc; r = 0.81). A significant mean underestimation of 11 ± 15 cc was noted ( p y = 0.89 x + 4; standard error of the estimate=6.7 cc; r = 0.96). However, the 3 ± 7 underestimation was significantly lower than the error of the ABD method ( p = 0.00005). Both on-line ABD and off-line ejection fractions correlated well with true ejection fractions ( r = 0.94 and 0.96, respectively). There was no statistically significant difference between the mean errors of the ABD or manually derived ejection fractions. In the setting of optimal left ventricular imaging, the on-line and rapid features of this automated method make it potentially useful for quickly obtaining left ventricular volumes and ejection fraction.