ECHOCARDIOGRAPHIC QUANTIFICATION OF REGIONAL LEFT-VENTRICULAR WALL-MOTION WITH COLOR KINESIS

Background Color kinesis is a new technology for the echocardiographic assessment of left ventricular wall motion based on acoustic quantifi cation. This technique automatically detects endocardial motion in rea l time by using integrated backscatter data to identify pixel transiti ons from blood to tissue during systole on a frame-by-frame basis, In this study, we evaluated the feasibility and accuracy of quantitative segmental analysis of color kinesis images to provide objective evalua tion of regional systolic endocardial motion. Methods and Results Two- dimensional echocardiograms were obtained in the short-axis and apical four-chamber views in 20 normal subjects and 40 patients with regiona l wall motion abnormalities. End-systolic color overlays superimposed on the gray scale images were obtained with color kinesis to color enc ode left ventricular endocardial motion throughout systole on a frame- by-frame basis. These color-encoded images were divided into segments by use of custom software. In each segment, pixels of different colors were counted and displayed as stacked histograms reflecting the magni tude and timing of regional endocardial excursion. In normal subjects, histograms were found to be highly consistent and reproducible. The p atterns of contraction obtained in normal subjects were used as a refe rence for the objective automated interpretation of regional wall moti on abnormalities, defined as deviations from this pattern. The variabi lity in the echocardiographic interpretation of wall motion between tw o experienced readers was similar to the diagnostic variability betwee n the consensus of the two readers and the automated interpretation. C onclusions Color kinesis is a promising new tool that may be used clin ically to improve the qualitative and quantitative evaluation of spati al and temporal aspects of global and regional wall motion. In this in itial study, segmental analysis of color kinesis images provided accur ate, automated, and quantitative diagnosis of regional wall motion abn ormalities.