Breast CT is an emerging modality that reconstructs 3D linear
attenuation coefficient (μ) images of the breast. Its
tomographic nature reduces the overlap of structures and may improve tissue
visualization. Current prototype systems produce large levels of scatter that
could be used to reconstruct electron density (ρ
$ _{e}$
)
images. This could potentially enhance diagnosis. We are developing a first
generation bench top CT system to investigate the benefits of simultaneous
imaging μ and ρ
$ _{e}$
of the intact
breast. The system uses an algorithm capable of reconstructing ρ
$_{e}$
images from single Klein-Nishina scatter. It has been suggested
that this algorithm may be impractical since measurements include coherent,
bound incoherent and multiple scatter. To investigate this, the EGSnrc Monte
Carlo (MC) code was used to simulate scans using a first generation system.
These simulations were used to quantify the dose per scan, to provide raw data
for the ρ
$ _{e}$
reconstructions and to investigate
corrections for multiple and coherent scatter since these can not be directly
related to ρ
$ _{e}$
. MC simulations show that the dose
coefficients are similar to those of cone beam breast CT. Coherent scatter is
only ∼9% concentrated in scattering angles
< 8°. Electron binding reduces the
number of incoherently scattered photons but this reduction can be included in
the quantification of scatter measured by the system. Multiple scatter was
found to be the major source of errors and, if not corrected for, can result in
an overestimation of ρ
$ _{e}$
by more than a factor of two.
Empirical corrections, based on breast thickness or radiological path, can be
used to reconstruct images where the variance in ρ
$ _{e}$
error is half of that found in images derived from primary photons only.
Although some practical challenges remain in creating a laboratory system, this
work has shown that it is possible to reconstruct scatter images of the breast
with a 4 mGy dose and further experimental evaluation of this technique is warranted.
