Automatic computation of left ventricular ejection fraction from spatiotemporal information in cine-SSFP cardiac MR images.

PURPOSE: To clinically validate an algorithm that automatically computes left ventricular (LV) ejection fraction (LVEF) using a priori geometric and intrinsic spatiotemporal information from cine steady-state free precession (SSFP) MR images.
MATERIALS AND METHODS: The algorithm was evaluated in 64 subjects (21 healthy volunteers and 43 patients, LVEF 19-71%). Bland-Altman analyses were performed on short-axis slices subdivided into three sections (basal, midcavity, and apical) to assess the impact of morphologic variations on LVEF computation.
RESULTS: The automated algorithm delineated the clinically applicable endocardial boundary in 1011 of 1078 short-axis slices (94%). The bias (mean difference) values computed with clinically unusable contours replaced with hand-drawn equivalents were small for the LV end-diastolic volume (LVEDV, <11 mL/7%), end-systolic volume (LVESV, <7 mL/11%), and LVEF (<1.2%). Moreover, these values were within the limits of interobserver and intraobserver variability of experienced observers (LVEDV, <13 mL/8%; LVESV, <12 mL/17%; and LVEF, <5%). In the end-diastolic phase, the limits of agreement (bias +/- 1.96 SD of difference) were small (<5% LVEDV) in all sections. However, in the end-systolic phase, the limits of agreement were larger for the midcavity (<21% LVESV) and apical (<11% LVESV) slices.
CONCLUSION: This data-driven algorithm can estimate LVEDV, LVESV, and LVEF with a bias that is comparable to the interobserver and intraobserver variability of experienced observers. (c) 2008 Wiley-Liss, Inc.