A D Nelson1, G J Muswick, R F Muzic, X Descamps. 1. Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, School of Medicine, Ohio 44106, USA.
Abstract
UNLABELLED: We present a myocardial edge detection technique that was developed for fast, reproducible measurements of left ventricular ejection fraction in the clinical setting. METHODS: This myocardial edge detection method compares three edge parameters--count amplitude and first and second count derivatives--in three consecutive locations along a radius to a predetermined template of these values. Each of the radii, defined at 10-degree intervals, has different template values that permit accurate edge detection even though adjacent structures, such as the left atrium and the right ventricle, alter edge parameters. The template for edge detection is based on either the average edge parameters determined from manually defined edges in 15 patients (automatic method) or an operator-defined edge in the first frame (semiautomatic method). RESULTS: The edge detection methods were tested in 100 patients, and intraobserver variabilities as well as comparison with clinically obtained ejection fractions were calculated. The standard error of the estimate was less than 3.1% for all observer comparisons. In 15 patients with both high-count (400,000 counts per image) and low count (50,000 counts per image) studies, the mean absolute difference in ejection fraction was 2.6% for intraobserver comparisons. CONCLUSION: A robust myocardial edge detection technique was developed that is applicable for routine clinical use.
UNLABELLED: We present a myocardial edge detection technique that was developed for fast, reproducible measurements of left ventricular ejection fraction in the clinical setting. METHODS: This myocardial edge detection method compares three edge parameters--count amplitude and first and second count derivatives--in three consecutive locations along a radius to a predetermined template of these values. Each of the radii, defined at 10-degree intervals, has different template values that permit accurate edge detection even though adjacent structures, such as the left atrium and the right ventricle, alter edge parameters. The template for edge detection is based on either the average edge parameters determined from manually defined edges in 15 patients (automatic method) or an operator-defined edge in the first frame (semiautomatic method). RESULTS: The edge detection methods were tested in 100 patients, and intraobserver variabilities as well as comparison with clinically obtained ejection fractions were calculated. The standard error of the estimate was less than 3.1% for all observer comparisons. In 15 patients with both high-count (400,000 counts per image) and low count (50,000 counts per image) studies, the mean absolute difference in ejection fraction was 2.6% for intraobserver comparisons. CONCLUSION: A robust myocardial edge detection technique was developed that is applicable for routine clinical use.
Authors: Wassila Djaballah; Marc A Muller; Anne C Bertrand; Pierre Y Marie; Bernard Chalon; Karim Djaballah; Pierre Olivier; Andreï Codreanu; Gilles Karcher; Alain Bertrand Journal: J Nucl Cardiol Date: 2005 Jan-Feb Impact factor: 5.952