Ultrafast Computation of Left Ventricular Ejection Fraction by Using Temporal Intensity Variation in Cine Cardiac Magnetic Resonance |
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Authors: | Amol S. Pednekar Benjamin Y.C. Cheong Raja Muthupillai |
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Affiliation: | 1. Philips Healthcare, Cleveland, Ohio ; 2. Department of Radiology, CHI St. Luke''s Health–Baylor St. Luke''s Medical Center, Houston, Texas ; 3. Department of Cardiology, Texas Heart Institute, Houston, Texas |
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Abstract: | Cardiac magnetic resonance enables comprehensive cardiac evaluation; however, intense time and labor requirements for data acquisition and processing have discouraged many clinicians from using it. We have developed an alternative image-processing algorithm that requires minimal user interaction: an ultrafast algorithm that computes left ventricular ejection fraction (LVEF) by using temporal intensity variation in cine balanced steady-state free precession (bSSFP) short-axis images, with or without contrast medium. We evaluated the algorithm''s performance against an expert observer''s analysis for segmenting the LV cavity in 65 study participants (LVEF range, 12%–70%). In 12 instances, contrast medium was administered before cine imaging. Bland-Altman analysis revealed quantitative effects of LV basal, midcavity, and apical morphologic variation on the algorithm''s accuracy.Total computation time for the LV stack was <2.5 seconds. The algorithm accurately delineated endocardial boundaries in 1,132 of 1,216 slices (93%). When contours in the extreme basal and apical slices were not adequate, they were replaced with manually drawn contours. The Bland-Altman mean differences were <1.2 mL (0.8%) for end-diastolic volume, <5 mL (6%) for end-systolic volume, and <3% for LVEF. Standard deviation of the difference was ≤4.1% of LV volume for all sections except the midcavity in end-systole (8.3% of end-systolic volume).We conclude that temporal intensity variation–based ultrafast LVEF computation is clinically accurate across a range of LV shapes and wall motions and is suitable for postcontrast cine SSFP imaging. Our algorithm enables real-time processing of cine bSSFP images on a commercial scanner console within 3 seconds in an unobtrusive automated process. |
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Keywords: | Algorithms automation cardiac volume/physiology image processing computer-assisted/methods magnetic resonance imaging cine/methods predictive value of tests reference values reproducibility of results ventricular dysfunction left/diagnosis |
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