Phantom
The simulated CT images were generated with the XCAT anthropomorphic digital phantom (Duke University, Durham, North Carolina, U.S.A.) at several inspiration levels and heart positions. This digital phantom provides a virtual model of patient anatomy and physiology including pulmonary vasculature and bronchopulmonary structures up to the terminal branches [1, 2]. The phantom allows for the specification of more than 200 parameters, including contrast administration, and respiratory and cardiac phase. This allows us to manipulate the voxel values representing different tissues with enhanced attenuation due to the presence of intravenous iodinated contrast agent. In this way, CT images could be simulated representing a patient being scanned at different respiratory and cardiac phases with and without contrast.
100 clinical subtraction CT pulmonary angiography (CTPA) cases from our institution were retrospectively evaluated to study clinical-relevant inspiration differences by measuring the difference in diaphragm positions between unenhanced and enhanced CT scans. It was found that the mean difference was 6 mm, with 20 mm being the 98th percentile. Therefore for the test cases three different diaphragm positions were used: 3 mm (small difference), 8 mm (approximately average clinical difference and closest available to 6 mm) and 20 mm (large difference). For the training set there are two other set of scans with similar diaphragm position (4 mm and 19 mm).
Moreover, we included two additional image sets:
1) We added titanium pins in the spine, therefore beam hardening occured
after CT simulation.
2) We increased and decreased the noise level of the CT simulation
All images have a related post- and pre-contrast scan. Make sure you
match the same to each other. In both situation we uploaded the
pre-contrast that has a 20 mm difference in diaphragm compared to the
post-contrast scan.
If you would like to work with the XCAT phantom, we would like to refer to the next two papers:
1. Segars, W.P., et al., 4D XCAT phantom for multimodality imaging research. Med Phys, 2010. 37(9): p. 4902-15.
2. Abadi, E., et al., Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins. IEEE Transactions on Medical Imaging, 2017. PP(99): p. 1-1.