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Multi-modality Breast Phantoms

 
 

Figure 1. 3D renderings of an initial breast model with the breast surface, pectoral muscle, and fibroglandular tissue.

Breast imaging is an important area of research with many new techniques being investigated to further reduce the morbidity and mortality of breast cancer through early detection. Computerized phantoms can provide an essential tool to evaluate and compare new imaging systems and techniques.


Current phantoms used in breast imaging research lack sufficient realism in depicting the complex three-dimensional (3D) anatomy of the breast; are frequently limited to a single application such as mammography; and do not have the flexibility to be applied to other emerging modalities such as tomosynthesis or CT. The four-dimensional (4D) extended cardiac-torso (XCAT) phantom was developed in our laboratory to provide a realistic and flexible model of the human anatomy and physiology. Previously limited to only a male anatomy, the  XCAT  was  recently  extended  to  include  a  detailed,  whole-body anatomy for  both  male and  female  subjects.

 
 
Figure 3. (A) Mammogram, (B) tomosynthesis, and (C) PEM images simulated from the compressed breast phantom as compared to patient images.

Despite this advancement, a current limitation to the phantom is that the female breast is modeled using only a simple outer surface and does not include any anatomical detail. As a result, the XCAT is severely limited in its application to breast imaging research where it may have a profound impact.

 

The goal of this work is to create a series of detailed 3D computational breast phantoms capable of realistically simulating a wide range of anatomical variations in health and disease with the flexibility to model different compression states of the breast for various imaging modalities; and to incorporate them seamlessly into the 4D XCAT phantom for breast imaging research.

 

Over a hundred anatomically diverse phantoms will be created based on high-resolution dedicated breast CT datasets obtained from Dr. John Boone at the University of California, Davis. The different breast tissues will be segmented from the CT datasets and then modeled using subdivision surfaces, tools widely used in computer graphics. When complete, the models will be capable of realistically simulating a wide range of anatomical variations in health and disease; and will include finite-element based techniques to simulate different compression states of the breast for various imaging modalities. Figure 1 shows an early-stage model of the breast phantom. Figures 2-3 show comparisons of actual patient data to simulated multi-modality imaging data generated from the phantom.

 

The work in this project will provide the necessary foundation to quantitatively evaluate and compare existing and emerging breast imaging devices and techniques. Unlike current, simplified breast models, the proposed phantoms, with the ability to simulate realistic, predictive patient imaging data from anatomically diverse subjects using different acquisition methods, would provide a more complete assessment of imaging techniques, not just in terms of simplified physical characteristics, but in terms of clinically relevant performance. As such, the phantoms will provide a unique and vital tool for breast imaging research.


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