BR3D Breast Imaging Phantom

Model 020

The CIRS Model 020 BR3D Breast Imaging Phantom assesses detectability of lesions of various sizes within a tissue equivalent, heterogeneous background.

In traditional 2D mammography, cancerous masses may be camouflaged by superposition of dense breast tissue. Tomosynthesis can help to eliminate this overlap by capturing multiple image “slices” of the breast that can be combined to create 3D reconstruction. As this new technology gains momentum in breast imaging, CIRS identified a need for a more realistic phantom to allow complex system checks.

Model 020 contains six heterogeneous, breast-equivalent slabs, which accurately demonstrate how underlying targets can be obscured by varying glandularity. Each slab consists of two tissue-equivalent materials mimicking 100% adipose and 100% gland tissues “swirled” together in an approximate 50/50 ratio by weight. Because each slab has a unique swirl pattern, the phantom can be arranged to create multiple backgrounds. One slab contains an assortment of microcalcifications, fibrils and masses and can be positioned at varying depths. Each semicircular-shaped slabs measure 100 x 180 x 10 mm.

Slabs with different gland-to-adipose ratios by weight are available by request.

  • Tests Tomosynthesis and Breast Computed Tomography
  • Complex background provides greater challenge for target detection
  • Slab configurations provide range of thicknesses with or without targets
  • Tissue equivalent adipose and gland tissues “swirled” in approximate 50/50 ratio by weight

Data Sheet

BR3D Breast Imaging Phantom: Data Sheet


Publication References

Feng SSJ, Sechopoulos I. A Software-Based X-Ray Scatter Correction Method for Breast Tomosynthesis. Medical Physics. 2011; 38(12):6643-6653. View

Taibi, A., et al., Lesion detectability in digital mammography and digital breast tomosynthesis: A Phantom Study. 2010; ECR Presentation B-823. View

Y.-H. Hu, D. A. Scaduto, W. Zhao, “Optimization of clinical protocols for contrast enhanced breast imaging,” in SPIE Medical Imaging (International Society for Optics and Photonics, 2013), p. 86680G–86680G. View

Gomi, T. (2015) Comparison of Different Reconstruction Algorithms for Decreasing the Exposure Dose during Digital Breast Tomosynthesis: A Phantom Study. J. Biomedical Science and Engineering, 8, 471-478. View

Han S. A Quantification Method for Breast Tissue Thickness and Iodine Concentration Using Photon-Counting Detector. J Digit Imaging. 2015;28(5):594-603. View

Adam Wang ; Edward Shapiro ; Sungwon Yoon ; Arundhuti Ganguly ; Cesar Proano, et al.
” Asymmetric scatter kernels for software-based scatter correction of gridless mammography “, Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94121I (March 18, 2015); doi:10.1117/12.2081501; View

David A. Scaduto ; Min Yang ; Jennifer Ripton-Snyder ; Paul R. Fisher and Wei Zhao
” Digital breast tomosynthesis with minimal breast compression “, Proc. SPIE9412, Medical Imaging 2015: Physics of Medical Imaging, 94121Y (March 18, 2015); doi:10.1117/12.2081543; View

Malliori A, Bliznakova K, Bliznakov Z, Cockmartin L, Bosmans H, Pallikarakis N. Breast tomosynthesis using the multiple projection algorithm adapted for stationary detectors. J Xray Sci Technol. 2016;24(1):23-41. View

Scaduto, D, et al. “Dependence of Contrast-Enhanced Lesion Detection in Contrast-Enhanced Digital Breast Tomosynthesis on Imaging Chain Design.” Springer Link, 17 June 2016. Web. View

Model: 020 Modality: