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An anthropomorphic breast model for breast imaging simulation and optimization.

Publication ,  Journal Article
Chen, B; Shorey, J; Saunders, RS; Richard, S; Thompson, J; Nolte, LW; Samei, E
Published in: Acad Radiol
May 2011

RATIONALE AND OBJECTIVES: Optimization studies for x-ray-based breast imaging systems using computer simulation can greatly benefit from a phantom capable of modeling varying anatomical variability across different patients. This study aimed to develop a three-dimensional phantom model with realistic and randomizable anatomical features. MATERIALS AND METHODS: A voxelized breast model was developed consisting of an outer layer of skin and subcutaneous fat, a mixture of glandular and adipose, stochastically generated ductal trees, masses, and microcalcifications. Randomized realization of the breast morphology provided a range of patient models. Compression models were included to represent the breast under various compression levels along different orientations. A Monte Carlo (MC) simulation code was adapted to simulate x-ray based imaging systems for the breast phantom. Simulated projections of the phantom at different angles were generated and reconstructed with iterative methods, simulating mammography, breast tomosynthesis, and computed tomography (CT) systems. Phantom dose maps were further generated for dosimetric evaluation. RESULTS: Region of interest comparisons of simulated and real mammograms showed strong similarities in terms of appearance and features. Noise-power spectra of simulated mammographic images demonstrated that the phantom provided target properties for anatomical backgrounds. Reconstructed tomosynthesis and CT images and dose maps provided corresponding data from a single breast enabling optimization studies. Dosimetry result provided insight into the dose distribution difference between modalities and compression levels. CONCLUSION: The anthropomorphic breast phantom, combined with the MC simulation platform, generated a realistic model for a breast imaging system. The developed platform is expected to provide a versatile and powerful framework for optimizing volumetric breast imaging systems.

Duke Scholars

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

May 2011

Volume

18

Issue

5

Start / End Page

536 / 546

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Nuclear Medicine & Medical Imaging
  • Monte Carlo Method
  • Models, Anatomic
  • Mammography
  • Humans
  • Computer Simulation
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Chen, B., Shorey, J., Saunders, R. S., Richard, S., Thompson, J., Nolte, L. W., & Samei, E. (2011). An anthropomorphic breast model for breast imaging simulation and optimization. Acad Radiol, 18(5), 536–546. https://doi.org/10.1016/j.acra.2010.11.009
Chen, Baiyu, Jamie Shorey, Robert S. Saunders, Samuel Richard, John Thompson, Loren W. Nolte, and Ehsan Samei. “An anthropomorphic breast model for breast imaging simulation and optimization.Acad Radiol 18, no. 5 (May 2011): 536–46. https://doi.org/10.1016/j.acra.2010.11.009.
Chen B, Shorey J, Saunders RS, Richard S, Thompson J, Nolte LW, et al. An anthropomorphic breast model for breast imaging simulation and optimization. Acad Radiol. 2011 May;18(5):536–46.
Chen, Baiyu, et al. “An anthropomorphic breast model for breast imaging simulation and optimization.Acad Radiol, vol. 18, no. 5, May 2011, pp. 536–46. Pubmed, doi:10.1016/j.acra.2010.11.009.
Chen B, Shorey J, Saunders RS, Richard S, Thompson J, Nolte LW, Samei E. An anthropomorphic breast model for breast imaging simulation and optimization. Acad Radiol. 2011 May;18(5):536–546.
Journal cover image

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

May 2011

Volume

18

Issue

5

Start / End Page

536 / 546

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Nuclear Medicine & Medical Imaging
  • Monte Carlo Method
  • Models, Anatomic
  • Mammography
  • Humans
  • Computer Simulation
  • 3202 Clinical sciences
  • 1103 Clinical Sciences