Lesion characterization in spectral photon-counting tomosynthesis

TL;DR

This study demonstrates that spectral tomosynthesis can potentially improve lesion characterization in breast imaging by providing 3D compositional information, reducing uncertainty from tissue interpolation compared to 2D spectral mammography.

Contribution

The paper shows that spectral tomosynthesis can be used for lesion characterization and investigates its potential to reduce tissue interpolation uncertainty, advancing 3D spectral imaging techniques.

Findings

Spectral tomosynthesis revealed compositional differences not visible in 2D.

Loss of discrimination signal was comparable to reduction of anatomical noise.

Preliminary clinical results were consistent with phantom experiments but inconclusive.

Abstract

It has previously been shown that 2D spectral mammography can be used to discriminate between (likely benign) cystic and (potentially malignant) solid lesions in order to reduce unnecessary recalls in mammography. One limitation of the technique is, however, that the composition of overlapping tissue needs to be interpolated from a region surrounding the lesion. The purpose of this investigation was to demonstrate that lesion characterization can be done with spectral tomosynthesis, and to investigate whether the 3D information available in tomosynthesis can reduce the uncertainty from the interpolation of surrounding tissue. A phantom experiment was designed to simulate a cyst and a tumor, where the tumor was overlaid with a structure that made it mimic a cyst. In 2D, the two targets appeared similar in composition, whereas spectral tomosynthesis revealed the exact compositional difference. However, the loss of discrimination signal due to spread from the plane of interest was of the same strength as the reduction of anatomical noise. Results from a preliminary investigation on clinical tomosynthesis images of solid lesions yielded results that were consistent with the phantom experiments, but were still to some extent inconclusive. We conclude that lesion characterization is feasible in spectral tomosynthesis, but more data, as well as refinement of the calibration and discrimination algorithms, are needed to draw final conclusions about the benefit compared to 2D.