Multicenter trial of automated border detection in cardiac MR imaging.

The purpose of the present study was to evaluate the robustness of a method of automated border detection in cardiac magnetic resonance (MR) imaging. Thirty-seven short-axis spin-echo cardiac images were acquired from three medical centers, each with its own image-acquisition protocol. Endo- and epicardial borders and areas were derived from these images with a graph-searching-based method of edge detection. Computer results were compared with observer-traced borders. The method accurately defined myocardial borders in 36 of 37 images (97%), with excellent agreement between computer- and observer-derived endocardial and epicardial areas (correlation coefficients, .94-.99). The algorithm worked equally well for data from all three centers, despite differences in image-acquisition protocols, MR systems, and field strengths. These data suggest that a method of computer-assisted edge detection based on graph-searching principles yields endocardial and epicardial areas that correlate well with those derived by an independent observer.