Differentiation of Lung Cancers From Inflammatory Masses with Dual-Energy Spectral CT Imaging

Rationale and Objectives: To investigate the value of dual-energy spectral computed tomography (DESCT) in the quantitative differentiation between pulmonary malignant masses and inflammatory masses. Materials and Methods: This study was an institutional review board-approved study, and written informed consent was obtained from all patients. Sixty patients with 35 lung cancers and 25 inflammatory masses underwent DESCT scan during arterial phase (AP) and venous phase (VP). CT numbers of net enhancement in 70 keV monochromatic images in central and peripheral regions of masses and their differences (dCT) were measured. Iodine concentrations in the two regions were measured and normalized to the aorta as normalized iodine concentrations (NICs). The slopes of spectral attenuation curves (lambda HU) in the two regions were also calculated. The two-sample t test was used to compare quantitative parameters. Receiver operating characteristic (ROC) curves were generated to calculate sensitivity and specificity. Results: CT numbers of net enhancement and NICs in central regions, and lambda HU values both in the central and peripheral region of lung cancers were significantly lower than those of inflammatory masses during AP and VP. On the other hand, the dCT values of lung cancers were higher than that of inflammatory masses. NIC value in the central regions in VP had the highest sensitivity (86%) and specificity (100%) in differentiating malignant masses from inflammatory masses. Conclusions: DESCT imaging with quantitative parameters such as CT numbers of 70 keV monochromatic images, NIC, and lambda HU may be a new method for differentiating lung cancers from inflammatory masses.