Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation

Authors

  • Sturgeon Gregory M.,

    1. Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705
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  • Kiarashi Nooshin,

    1. Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708
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  • Lo Joseph Y.,

    1. Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705; and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708
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  • Samei E.,

    1. Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705; Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708; and Department of Physics, Duke University, Durham, North Carolina 27708
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  • Segars W. P.

    1. Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
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Abstract

Purpose:

The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging.

Methods:

This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast.

Results:

The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts.

Conclusions:

The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast.

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