We evaluated attenuation-based 3-dimensional segmentation for the analysis of left ventricular function, using as our standard of reference magnetic resonance imaging and dual-source computed tomography with traditional short-axis planimetry.Twenty patients with known or suspected coronary artery disease were examined prospectively. In all magnetic resonance and computed tomographic datasets, global functional values were determined by 2-dimensional planimetry. Computed tomographic scans were further evaluated by automated 3-dimensional segmentation, and the results were compared by Pearson correlation and Bland-Altman analysis.Agreement between magnetic resonance imaging and dual-source computed tomographic 2-dimensional planimetry was good for all values (end-diastolic volume, bias= -4.2, r=0.99; end-systolic volume, bias= -1.7, r=0.99, stroke-volume, bias= -2.4, r=0.98; ejection fraction, bias=0.26, r=0.94; and myocardial mass, bias= 2.5, r=0.90). By contrast, dual-source computed tomographic 3-dimensional segmentation overestimated end-diastolic volume (bias= -19.1, P <0.001), stroke-volume (bias= -16.9, P <0.001), and myocardial mass (bias= -34.4, P <0.001). Moreover, correlation with magnetic resonance imaging proved disappointing for ejection fraction (r=0.72). Results were similar in a direct comparison between dual-source computed tomographic 2-dimensional planimetry and 3-dimensional segmentation (end-diastolic volume, bias= -14.9, r=0.94; end-systolic volume, bias= -0.5, r=0.90; stroke volume, bias= -14.5, r=0.83; ejection fraction, bias= -2.8, r=0.74; and myocardial mass, bias= -36.8, r=0.79).Due to significant overestimation of volumes and poor correlation of ejection fraction with cine magnetic resonance imaging results, attenuation-based 3-dimensional segmentation compares unfavorably with traditional planimetry. Hence this method should be used with caution, and its time benefits should be weighed against its imprecision of functional analysis.
Keywords: Cardiovascular magnetic resonance; hypertrophy, left ventricular/diagnosis; magnetic res-onance imaging, cine; magnetic resonance angiography; models, cardiovascular; pattern recognition, automated/methods; prospective studies; radiographic image enhancement/methods; radiographic image interpretation, computer-assisted; tomography, x-ray computed; ventricular dysfunction, left/diagnosis/radiography.