Insertion of virtual pulmonary nodules in CT data of the chest: development of a software tool

The purpose of this study was to develop a software tool for the insertion of virtual lung nodules into CT data. Forty software-generated nodules were inserted at random locations and sizes on 20 multi-detector row CT studies of the chest (4 x 1-2.5-mm slice collimation). On each scan, two virtual nodules were inserted. The size, shape, margin and attenuation could arbitrarily vary and were individually adjusted to match real lesions of each patient (real nodules: 6.5+/-3.1 mm; virtual nodules: 6.1+/-3.2 mm). Additionally, noise and a random pattern simulating local density variations were added to virtual nodules. Three blinded readers evaluated 40 real and 40 simulated nodules according to a 5-point confidence scale ranging from 1 (definitely simulated) to 5 (definitely real). A multivariate analysis of covariance was performed for statistical assessment (SPSS 11.5, Chicago, IL). Real and simulated lesions were indistinguishable for all three readers (Pillai's trace statistic: P=0.881). However, nodule size was a statistically significant covariable regarding the differentiation of virtual compared to real nodules. Larger simulated nodules were easier to detect than smaller ones (Pillai's trace statistic: P<0.05). The developed algorithm allowed for the synthetic generation of lung nodules that were indistinguishable from real nodules.