In developing breast imaging technologies, testing is done with phantoms. Physical phantoms are normally used but their size, shape, composition, and detail cannot be modified readily. These difficulties can be avoided by creating a software breast phantom. Researchers have created software breast phantoms using geometric and/or mathematical methods for applications like image fusion. The authors report a 3D software breast phantom that was built using a mechanical design tool, to investigate the biomechanics ofelastography using finite element modeling (FEM). The authors propose this phantom as an intermediate assessment tool for elastography simulation; for use after testing with commonly used phantoms and before clinical testing. The authors design the phantom to be flexible in both, the breast geometry and biomechanical parameters, to make it a useful tool for elastography simulation.Methods:
The authors develop the 3D software phantom using a mechanical design tool based on illustrations of normal breast anatomy. The software phantom does not use geometric primitives or imaging data. The authors discuss how to create this phantom and how to modify it. The authors demonstrate a typicalelastography experiment of applying a static stress to the top surface of the breast just above a simulated tumor and calculate normal strains in 3D and in 2D with plane strain approximations with linear solvers. In particular, they investigate contrast transfer efficiency (CTE) by designing a parametric study based on location, shape, and stiffness of simulated tumors. The authors also compare their findings to a commonly used elastography phantom.Results:
The 3D breast software phantom is flexible in shape, size, and location of tumors, glandular to fatty content, and the ductal structure. Residual modulus, maps, and profiles, served as a guide to optimize meshing of this geometrically nonlinear phantom for biomechanical modeling ofelastography. At best, low residues (around 1–5 KPa) were found within the phantom while errors were elevated (around 10–30 KPa) at tumor and lobule boundaries. From our FEM analysis, the breast phantom generated a superior CTE in both 2D and in 3D over the block phantom. It also showed differences in CTE values and strain contrast for deep and shallow tumors and showed significant change in CTE when 3D modeling was used. These changes were not significant in the block phantom. Both phantoms, however, showed worsened CTE values for increased input tumor-background modulus contrast.Conclusions:
Block phantoms serve as a starting tool but a next level phantom, like the proposed breast phantom, will serve as a valuable intermediate forelastography simulation before clinical testing. Further, given the CTE metrics for the breast phantom are superior to the block phantom, and vary for tumor shape, location, and stiffness, these phantoms would enhance the study of elastography contrast. Further, the use of 2D phantoms with plane strain approximations overestimates the CTE value when compared to the true CTE achieved with 3D models. Thus, the use of 3D phantoms, like the breast phantom, with no approximations, will assist in more accurate estimation of modulus, especially valuable for 3D elastography systems.
II. BREAST ANATOMY
III. 3D BREAST MODEL
III.A. Breast phantom detail
III.B. Measurements and specifications
IV. BIOMECHANICAL MODELING
IV.A. Elastography: Typical experiment
IV.B. Constitutive equations for FEM
IV.C. Finite element model settings
IV.C.1. Material properties
IV.C.2. Meshing strategies
IV.C.3. Solver settings
IV.C.4. Boundary conditions
V. RESULTS AND DISCUSSION
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