Quantitative assessment of temporal and spatial ventricular wall motion in normal and infarcted human left ventricles

Variability in frame by frame analysis of left ventricular wall motion from contrast angiograms

BACKGROUND

Measurement of the timing of left ventricular (LV) wall motion, of asynchrony, and of diastolic function from contrast angiograms requires delineation of the endocardial border frame by frame through the cardiac cycle. This study was performed to determine the magnitude of intraobserver and interobserver variability in manual border tracing, and to measure the impact of this variability on the derived functional parameters.

METHODS

The contrast ventriculograms of 25 patients with coronary artery disease (CAD) or with normal coronary arteries were analyzed frame by frame, by two observers or twice by the same observer. Motion was measured using the centerline method at each twelfth of systole and of diastole. Variability was calculated as the absolute difference between repeated measurements of: wall motion, asynchrony, and the time at which each region of the LV reached 10%, 50%, and 100% of peak contraction, and 50% of filling.

RESULTS

Intraobserver and interobserver variability in wall motion were similar, and varied with time in the cycle, and with location on the LV contour. Variability was highest at end systole, when it averaged 8% of the normal mean for wall motion. Variability in timing was highest at peak contraction; however, the variability in measuring asynchrony averaged only 18 msec.

CONCLUSION

Analysis of the magnitude and synchrony of regional LV wall motion through the cardiac cycle from contrast ventriculograms can be performed with reproducibility comparable to that at end systole.

Identifying and tracking a guide wire in the coronary arteries during angioplasty from X-ray images

During angioplasty, a guide wire (GW) is routinely placed in the coronary artery. Balloon inflation during angioplasty causes transient occlusion of the coronary artery and regional dysfunction. Thus, it is of major importance to monitor myocardial function, which may be impaired during this period. Since the GW moves with the coronary arteries, information regarding myocardial function can potentially be extracted from the GW motion. An algorithm is suggested which is a step toward such monitoring. The algorithm presented is a semiautomatic procedure for identifying and tracking the GW using specific characteristics of the GW. This algorithm is based on working in limited active windows. A preprocessing stage which enhances the GW by the use of a modified Laplacian filter or a modified Marr-Hildreth filter is introduced. The second stage of the algorithm is the tracking of the GW, which is based on fitting a second-degree polynomial to the GW using the Hough transform in each window. To further improve the results further modifications of the basic algorithms that were taken. A single set of parameters, which enabled good tracking for a large number of images taken during angioplasty, was fitted to the final algorithm.