A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications

Abstract

Many important post-acquisition aspects of breast tomosynthesis imaging can impact its clinical performance. Chief among them is the reconstruction algorithm that generates the representation of the three-dimensional breast volume from the acquired projections. But even after reconstruction, additional processes, such as artifact reduction algorithms, computer aided detection and diagnosis, among others, can also impact the performance of breast tomosynthesis in the clinical realm. In this two part paper, a review of breast tomosynthesis research is performed, with an emphasis on its medical physics aspects. In the companion paper, the first part of this review, the research performed relevant to the image acquisition process is examined. This second part will review the research on the post-acquisition aspects, including reconstruction, image processing, and analysis, as well as the advanced applications being investigated for breast tomosynthesis.

Figure 1

Modification of ramp filter to maintain the low frequency information in FBP reconstructed DBT images. Reprinted with permission from Zhou et al., “A computer simulation platform for the optimization of a breast tomosynthesis system,” Med. Phys. 34(3), 1098–1109 (2007). Copyright © 2007, American Association of Physicists in Medicine (AAPM).

Figure 2

Typical reconstruction artifacts found in DBT from out-of-plane high contrast objects (left) and the result of the correction proposed by Wu et al. (right). These examples show artifacts from a localization needle (top) and large microcalcifications (bottom). Reprinted with permission from Wu et al., “Voting strategy for artifact reduction in digital breast tomosynthesis,” Med. Phys. 33(7), 2461–2471 (2006). Copyright © 2006, American Association of Physicists in Medicine.

Figure 3

Result of the correction proposed by Zhang et al. to remove the breast boundary artifacts (arrows) from DBT reconstructions. Reprinted with permission from Zhang et al., “Application of boundary detection information in breast tomosynthesis reconstruction,” Med. Phys. 34(9), 3603–3613 (2007). Copyright © 2007, American Association of Physicists in Medicine (AAPM).

Figure 4

Diagram of a typical DBT acquisition showing the source of two reconstruction artifacts. The gray areas show portions of the breast tissue that cause artifacts near the borders of the reconstructed volume (dashed box) in the x-ray tube motion direction. Examples of both of these artifacts can be seen at the top of the left image in Fig. 5; the bright area is due to the gray portion of breast tissue on the left of the diagram, while the horizontal stripes are due to the gray portion of breast tissue on the right.

Figure 5

Result of the algorithm proposed by Zhang et al. to reduce the detector boundary artifact commonly seen in DBT reconstructions. Reprinted with permission from Zhang et al., “Artifact reduction methods for truncated projections in iterative breast tomosynthesis reconstruction,” J. Comput. Assist. Tomogr. 33(3), 426–435 (2009). Copyright © 2009, Lippincott Williams & Wilkins.

Figure 6

(a) Digital mammogram (MLO view) of a patient showing two malignant masses, (b) synthetic mammogram constructed from the DBT data, (c) DBT slice. Reprinted with permission from Gur et al., “Dose reduction in digital breast tomosynthesis (DBT) screening using synthetically reconstructed projection images: An observer performance study,” Acad. Radiol. 19(2), 166–171 (2012). Copyright © 2012, Association of University Radiologists (AUR).

Figure 7

ROI of a contrast enhanced DBT reconstruction of a patient with a malignant mass. (Left) Dual energy subtraction; (right) temporal subtraction. The presence of motion in the temporal subtraction is apparent. Reprinted with permission from Carton et al., “Dual-energy contrast-enhanced digital breast tomosynthesis: A feasibility study,” Br. J. Radiol. 83(988), 344–350 (2010). Copyright © 2010, The British Institute of Radiology.