Physical breast phantoms provide a standard method to test, optimize, and develop clinical mammography systems, including new digital breast tomosynthesis (DBT) systems. In previous work, we produced an anthropomorphic phantom based on 500x500x500 μm breast CT data using commercial 3D printing. We now introduce an improved phantom based on a new cohort of virtual models with 155x155x155 μm voxels and fabricated through voxelized 3D printing and dithering, which confer higher resolution and greater control over contrast. This new generation includes a uniform chest wall extension for evaluating conventional QC metrics. The uniform region contains a grayscale step wedge, chest wall coverage markers, fiducial markers, spheres, and metal ink stickers of line pairs and edges to assess contrast, resolution, artifact spread function, MTF, and other criteria. We also experimented with doping photopolymer material with calcium, iodine, and zinc to increase our current contrast. In particular, zinc was discovered to significantly increase attenuation beyond 100% breast density with a linear relationship between zinc concentration and attenuation or breast density. This linear relationship was retained when the zinc-doped material was applied in conjunction with 3D printing. As we move towards our long term goal of phantoms that are indistinguishable from patients, this new generation of anthropomorphic physical breast phantom validates our voxelized printing process, demonstrates the utility of a uniform QC region with features from 3D printing and metal ink stickers, and shows potential for improved contrast via doping.
Christine Zhao, Justin Solomon, Gregory M. Sturgeon, Michael E. Gehm, Matthew Catenacci, Benjamin J. Wiley, Ehsan Samei, and Joseph Y. Lo, "Third generation anthropomorphic physical phantom for mammography and DBT: incorporating voxelized 3D printing and uniform chest wall QC region," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321Y (Presented at SPIE Medical Imaging: February 16, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2256091.
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