This study aimed to model virtual human lung phantoms including both non-parenchymal and parenchymal structures. Initial branches of the non-parenchymal structures (airways, arteries, and veins) were segmented from anatomical data in each lobe separately. A volume-filling branching algorithm was utilized to grow the higher generations of the airways and vessels to the level of terminal branches. The diameters of the airways and vessels were estimated using established relationships between flow rates and diameters. The parenchyma was modeled based on secondary pulmonary lobule units. Polyhedral shapes with variable sizes were modeled, and the borders were assigned to interlobular septa. A heterogeneous background was added inside these units using a non-parametric texture synthesis algorithm which was informed by a high-resolution CT lung specimen dataset. A voxelized based CT simulator was developed to create synthetic helical CT images of the phantom with different pitch values. Results showed the progressive degradation in depiction of lung details with increased pitch. Overall, the enhanced lung models combined with the XCAT phantoms prove to provide a powerful toolset to perform virtual clinical trials in the context of thoracic imaging. Such trials, not practical using clinical datasets or simplistic phantoms, can quantitatively evaluate and optimize advanced imaging techniques towards patient-based care.
Ehsan Abadi, Gregory M. Sturgeon, Greeshma Agasthya, Brian Harrawood, Christoph Hoeschen, Anuj Kapadia, W. Paul Segars, and Ehsan Samei, "Airways, vasculature, and interstitial tissue: anatomically informed computational modeling of human lungs for virtual clinical trials," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321Q (Presented at SPIE Medical Imaging: February 16, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2254739.
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