Automated assessment of left ventricular wall motion based on surface detection and color-encoding of real time three-dimensional echocardiographic images

Off-line 3D color-encoding was applied to the left ventricular (LV) endocardial surfaces obtained from real-time 3D echocardiographic images. Systolic regional wall motion abnormalities (RWMA) were automatically detected and the accuracy of this method was tested against expert visual interpretation of 2D echocardiographic (2DE) images (apical 2-, 3- and 4- chamber). 20 subjects with normal wall motion (NL), and 14 patients with RWMA were studied. By custom software, color-coded 3D images of systolic wall motion were created, and regional fractional volume change (RFVC) in % of regional end diastolic volume was calculated (18 segments model). In the RWMA pts, RFVCs were compared with thresholds derived from NL subjects for automated classification of the corresponding segments as normal or abnormal. The proposed technique agreed with the expert reader with 91% sensitivity, 80% specificity and 84% accuracy.