Does multi-detector row CT with semiautomated analysis software accurately measure left ventricular volumes and function compared to MR imaging in patients with known or suspected coronary artery disease?
Multi-detector row CT with semiautomated analysis software provides accurate measurements of left ventricular volumes and function that correlate well with MR imaging.
PURPOSE: To determine left ventricular (LV) volumetric and functional parameters from retrospectively electrocardiographically gated multi-detector row computed tomography (CT) by using semiautomated analysis software and to correlate results with those of magnetic resonance (MR) imaging. MATERIALS AND METHODS: In 30 patients (mean age, 59.2 years +/- 7.1 SD) known to have or suspected of having coronary artery disease, four-channel multi-detector row CT was performed with standard technique, and diastolic and systolic image reconstructions were generated. With commercially available analysis software capable of semiautomated contour detection, end diastolic and end systolic LV volumes were determined from short-axis secondary CT reformations. Steady-state free-precession cine MR images were acquired in short-axis orientation within 48 hours and analyzed by using dedicated software. Bland-Altman analysis was performed to calculate limits of agreement and systematic errors between CT and MR imaging. RESULTS: Mean end diastolic (138.8 mL +/- 31.9) and end systolic (53.9 mL +/- 21.2) LV volumes as determined with CT correlated well with MR imaging measurements (142.0 mL +/- 32.5 r = 0.93 and 54.9 mL +/- 22.8 r = 0.94, respectively P <.001). LV ejection fraction (61.6% +/- 10.6 for CT vs 62.3% +/- 10.1 for MR imaging; r = 0.89) and stroke volume (84.6 mL +/- 20.9 for CT vs 86.9 mL +/- 21.5 for MR imaging; r = 0.88) also showed good correlation (P <.001). Bland-Altman analysis showed acceptable limits of agreement (+/-9.8% for ejection fraction) without systematic errors. CONCLUSION: In selected patients, semiautomated analysis software enables LV volumetric and functional analysis based on multi-detector row CT data sets, the results of which correlate well with MR imaging findings.
Juergens et al. (2004) studied this question.