Evaluation of manual and automatic segmentation of the mouse heart from CINE MR images

Abstract

To compare global functional parameters determined from a stack of cinematographic MR images of mouse heart by a manual segmentation and an automatic segmentation algorithm. The manual and automatic segmentation results of 22 mouse hearts were compared. The automatic segmentation was based on propagation of a minimum cost algorithm in polar space starting from manually drawn contours in one heart phase. Intra- and interobserver variability as well as validity of the automatic segmentation was determined. To test the reproducibility of the algorithm the variability was calculated from the intra- and interobserver input. The mean time of segmentation for one dataset was around 10 minutes and approximately 2.5 hours for automatic and manual segmentation, respectively. There were no significant differences between the automatic and the manual segmentation except for the end systolic epicardial volume. The automatically derived volumes correlated well with the manually derived volumes (R(2) = 0.90); left ventricular mass with and without papillary muscle showed a correlation R(2) of 0.74 and 0.76, respectively. The manual intraobserver variability was superior to the interobserver variability and the variability of the automatic segmentation, while the manual interobserver variability was comparable to the variability of the automatic segmentation. The automatic segmentation algorithm reduced the bias of the intra- and interobserver variability. We conclude that automatic segmentation of the mouse heart provides a fast and valid alternative to manual segmentation of the mouse heart.