Simulated magnetic resonance imaging brain studies have been generated for over a decade. Despite their useful potential, simulated cardiac studies are only emerging. This article focuses on the realistic simulation of cardiac magnetic resonance imaging datasets. The methodology is based on the XCAT phantom, which is modified to increase realism of the simulated images. Modifications include the modeling of trabeculae and papillary muscles based on clinical measurements and published data. To develop and evaluate our approach, the clinical database included 40 patients for anatomical measurements, 10 patients for papillary muscle modeling, and 10 patients for local gray value statistics. The virtual database consisted of 40 digital voxel phantoms. Histograms from different tissues were obtained from the real datasets and compared with histograms of the simulated datasets with the Chi-square dissimilarity metric (χ(2)) and Kullback-Leibler divergence. For the original phantom, χ(2) values averaged 0.65 ± 0.06 and Kullboek-Leibler values averaged 0.69 ± 0.38. For the modified phantom, χ(2) values averaged 0.34 ± 0.12 and Kullboek-Leibler values averaged 0.32 ± 0.15. The proposed approach demonstrated a noticeable improvement of the local appearance of the simulated images with respect to the ones obtained originally.
© 2010 Wiley-Liss, Inc.