Tissue superimposition is a challenge in mammography. Providing 3D images of the breast, Digital Breast Tomosynthesis can relieve this issue. The angle used for Digital Breast Tomosynthesis plays an important role in how strong overlapping tissue can be reduced. We are convinced that a wide-angle system is the best possible solution.
Principles of the wide angle
The figure illustrates that, depending on the position of the X-ray source, the single projections will show the black and white spheres with more or less overlap. The wider the angle, the better the two spheres can be separated.
Delivering a higher depth resolution, a wider angle can better reduce superimposition of breast tissue. This has been proven in many scientific studies, for example1-3, and also by researchers from the FDA4.
How the angle affects the depth resolution
Comparing different angles shows how accurately the location of a hypothetical circular lesion can be determined. A 2D FFDM provides no information on the spatial location of the lesion, meaning the lesion could be at any height. The wider the tomosynthesis angle, the smaller becomes the height-probability area, indicating that the lesion can be located with increased precision.
How the angle affects the image contrast
A wider scan angle also improves the detection of large-area low-contrast lesions like breast masses. From a physics point of view, these masses are low-frequency objects in the Fourier space. The sampling of these low frequencies is much better with a wide angle and will result in a higher image contrast. This improvement in mass detection performance has been confirmed in many studies.2;5-9
Zhou J, Zhao B, Zhao W (2007) A computer simulation platform for the optimization of a breast tomosynthesis system. Medical physics 34(3):1098–109.
Mertelmeier T, Ludwig J, Zhao B, Zhao W (2008) Optimization of Tomosynthesis Acquisition Parameters: Angular Range and Number of Projections. In: Krupinski EA (ed) Digital Mammography. Springer Berlin Heidelberg. Berlin, Heidelberg, pp 220–227.
Sechopoulos I, Ghetti C (2009) Optimization of the acquisition geometry in digital tomosynthesis of the breast. Medical physics 36(4):1199–207.
Zeng R, Park S, Bakic P, Myers KJ (2015) Evaluating the sensitivity of the optimization of acquisition geometry to the choice of reconstruction algorithm in digital breast tomosynthesis through a simulation study. Physics in medicine and biology 60(3):1259–88.
Zhao B, Zhou J, Hu Y-H, Mertelmeier T, Ludwig J, Zhao W (2009) Experimental validation of a three-dimensional linear system model for breast tomosynthesis. Medical physics 36(1):240–51.
Chawla AS, Lo JY, Baker JA, Samei E (2009) Optimized image acquisition for breast tomosynthesis in projection and reconstruction space. Medical physics 36(11):4859–69.
van de Sompel D, Brady SM, Boone JM (2011) Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers. Medical image analysis 15(1):53–70.
Reiser IS, Nishikawa RM (2010) Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise. Medical physics 37(4):1591–600.
Endo T, Morita T, Oiwa M, Suda N, Sato Y, Ichihara S et al. (2016) Detectability comparison of modes in dual-mode digital breast tomosynthesis. Breast cancer (Tokyo, Japan). doi:10.1007/s12282-016-0725-0.