COPD quantifications via CT imaging: ascertaining the effects of acquisition protocol using virtual imaging trial

COPD is the fourth leading cause of death in the United States. The structural and functional attributes of this disease can be assessed in vivo using computed tomography (CT). The value of quantitative CT has been demonstrated towards characterization and treatment evaluation of COPD. Although promising, the influence of imaging protocols on the accuracy and precision of these quantifications remains unknown. The purpose of this study was to build a novel and realistic virtual imaging platform and investigate the effects of CT imaging parameters on COPD quantifications. Ten COPD human models were created on the platform of the state-of-the-art XCAT human models. The shape, size, and the distribution of emphysema along with its material density were modeled separately in each XCAT phantom, based on the CT images of confirmed COPD patients. The developed phantoms were imaged using an established scanner-specific CT simulator (DukeSim) at various dose levels with and without tube current modulation. The projection images were then reconstructed using six different reconstructions from a commercial reconstruction toolbox. Established COPD imaging biomarkers were extracted from the simulated images and compared against their corresponding digital ground truth values. The relative bias ranged from -2.1% to 66.0% and the variability ranged from 0.9% to 29.5%. The results showed that with careful choice of smooth reconstruction kernel, CT can be used as a reliable quantification tool for the COPD, with higher mAs, fixed tube currents, and iterative reconstructions further enhancing the accurate and consistent quantification of the disease. This study demonstrates the first development of a suite of computational COPD phantoms, enabling virtual imaging trials in the context of COPD imaging.