Dual-energy contrast-enhanced digital breast tomosynthesis (DE
CE-DBT) image quality is affected by a large parameter
space including the tomosynthesis acquisition geometry, imaging technique factors, the choice of reconstruction
algorithm, and the subject breast characteristics. The influence of most of these factors on reconstructed image quality is
well understood for DBT. However, due to the contrast agent uptake kinetics in CE imaging, the subject breast
characteristics change over time, presenting a challenge for optimization . In this work we experimentally evaluate the
sensitivity of the reconstructed image quality to timing of the
low-energy and high-energy images and changes in iodine
concentration during image acquisition. For four contrast uptake patterns, a variety of acquisition protocols were tested
with different timing and geometry. The influence of the choice of reconstruction algorithm (SART or FBP) was also
assessed. Image quality was evaluated in terms of the lesion
signal-difference-to-noise ratio (LSDNR) in the central slice
of DE CE-DBT reconstructions. Results suggest that for maximum image quality, the low- and high-energy image
acquisitions should be made within one x-ray tube sweep, as separate low- and high-energy tube sweeps can degrade
LSDNR. In terms of LSDNR per square-root dose, the image quality is nearly equal between SART reconstructions with
9 and 15 angular views, but using fewer angular views can result in a significant improvement in the quantitative
accuracy of the reconstructions due to the shorter imaging time interval.
Dual-energy contrast-enhanced digital breast tomosynthesis (CE-DBT) using an iodinated contrast agent is an imaging
technique providing 3D functional images of breast lesion vascularity and tissue perfusion. The iodine uptake in the
breast is very small and causes only small changes in x-ray transmission; typically less than 5%. This presents
significant technical challenges on the imaging system performance. The purpose of this paper was to characterize
image lag and scattered radiation and their effects on image quality for dual-energy CE-DBT using a CsI(Tl) phosphor-based
detector. Lag was tested using typical clinical acquisition sequences and exposure parameters and under various
detector read-out modes. The performance of a prototype anti-scatter grid and its potential benefit on the magnitude and
range of the cupping artifact were investigated. Analyses were performed through phantom experiments. Our results
illustrate that the magnitude of image lag is negligible and breast texture cancelation is almost perfect when the detector
is read out several times between x-ray exposures. The anti-scatter grid effectively reduces scatter and the cupping
artifact.
With the injection of iodine, Contrast Enhanced Digital Mammography (CEDM) provides functional information
about breast tumour angiogenesis that can potentially help in cancer diagnosis. In order to generate iodine images
in which the gray level is proportional to the iodine thickness, temporal and dual-energy approaches have already
been considered. The dual-energy method offers the advantage of less patient motion artifacts and better comfort
during the exam. However, this approach requires knowledge of the breast thickness at each pixel. Generally, as
compression is applied, the breast thickness at each pixel is taken as the compression thickness. Nevertheless,
in the breast border region, this assumption is not correct anymore and this causes inaccuracies in the iodine
image. Triple-Energy CEDM could overcome these limitations by providing supplemental information in the
form of a third image acquired with a different spectrum than the other two. This precludes the need of a priori
knowledge of the breast thickness. Moreover, with Triple-Energy CEDM, breast thickness and glandularity maps
could potentially be derived. In this study, we first focused on the method to recombine the three images in
order to generate the iodine image, analyzing the performance of either quadratic, cubic or conic recombination
functions. Then, we studied the optimal acquisition spectra in order to maximize the iodine SDNR in the
recombined image for a given target total glandular dose. The concept of Triple-Energy CEDM was validated on
simulated textured images and poly-energetic images acquired with a conventional X-ray mammography tube.
Dual-energy imaging with the injection of an iodinated contrast medium has the potential to depict cancers in the breast, by the demonstration of tumour angiogenesis and the suppression of the breast structure noise. The present study investigates the optimum monoenergetic beam parameters for this application. First, a theoretical study of the beam parameters was performed to find the best compromise between the quality of the dualenergy
recombined image and the patient dose. The result of this analysis was then validated by phantom experiments using synchrotron monoenergetic radiation at the European Synchrotron Radiation Facility (ESRF, Grenoble, France). For an average breast of 5cm thickness and 50% glandularity, the theoretical simulations
show an optimum at 20 keV for the low energy and 34 keV for the high energy, for a CsI detector of a standard mammography system. The SDNR variations with the low energy, the high energy or the dose repartition are very similar between the measurements on images acquired with synchrotron radiation and the simulated values.
This ensures the accuracy of our theoretical optimization and the validity of the optimal beam parameters found in this study. The aim of this work is to demonstrate the potential of Dual-Energy CEDM (Contrast Enhanced Digital Mammography) with ideal monoenergetic sources, in order to provide an indicator of how to shape the
polyenergetic spectra produced with classical X-ray sources for this application.
KEYWORDS: Iodine, Breast, Sensors, Point spread functions, Signal attenuation, Image quality, X-rays, Digital breast tomosynthesis, Tissues, Digital mammography
Dual-Energy Contrast Enhanced Digital Breast Tomosynthesis (DE CEDBT) is a promising technique for breast
cancer detection, which combines the strengths of functional and 3D imaging. In the present study, we first
focused on the optimization of the acquisition parameters for the low and high-energy projections, which leads
to a trade-off between image quality in the recombined slices and the Average Glandular Dose (AGD) delivered
to the patient. Optimized parameters were found and experimentally validated on phantom images. Then, we
addressed the problem of iodine quantification in the recombined slices. In DE CEDBT, iodine quantification is
limited by the z-resolution, due to the restricted angle acquisition inherent to tomosynthesis. We evaluated the
lesion thickness above which determination of iodine volumetric concentration is possible. For lesions below this
thickness, estimation of iodine concentration is possible if a priori information or a model on the shape of the
lesion is available. Iodine quantification for lesions located near the breast boundary is also challenging, due to
scatter border effects and variation of the breast thickness in this region. A scatter correction algorithm based
on a deconvolution scheme and a thickness compensation algorithm were applied on the low and high-energy
projections. Corrected images showed a more accurate quantification of iodine.
KEYWORDS: Iodine, Reconstruction algorithms, Breast, Digital breast tomosynthesis, Tomography, Manganese, X-rays, Sensors, Signal to noise ratio, Visibility
In this paper, we present the development of dual-energy Contrast-Enhanced Digital Breast Tomosynthesis
(CEDBT). A method to produce background clutter-free slices from a set of low and high-energy projections
is introduced, along with a scheme for the determination of the optimal low and high-energy techniques. Our
approach consists of a dual-energy recombination of the projections, with an algorithm that has proven its performance
in Contrast-Enhanced Digital Mammography1 (CEDM), followed by an iterative volume reconstruction.
The aim is to eliminate the anatomical background clutter and to reconstruct slices where the gray level is
proportional to the local iodine volumetric concentration. Optimization of the low and high-energy techniques
is performed by minimizing the total glandular dose to reach a target iodine Signal Difference to Noise Ratio
(SDNR) in the slices. In this study, we proved that this optimization could be done on the projections, by
consideration of the SDNR in the projections instead of the SDNR in the slices, and verified this with phantom
measurements. We also discuss some limitations of dual-energy CEDBT, due to the restricted angular range
for the projection views, and to the presence of scattered radiation. Experiments on textured phantoms with
iodine inserts were conducted to assess the performance of dual-energy CEDBT. Texture contrast was nearly
completely removed and the iodine signal was enhanced in the slices.
In this study, we propose a novel approach to dual-energy
contrast-enhanced digital mammography, with the development of a
dual-energy recombination algorithm based on an image chain model
and the determination of the associated optimal low and high-energy
techniques. Our method produces clutter-free iodine-equivalent
images and includes thickness correction near the breast border.
After the algorithm description, the optimal low and high-energy
acquisition techniques are determined to obtain a compromise between
image quality and glandular dose. The low and high-energy techniques
were chosen to minimize the glandular dose for a target Signal
Difference to Noise Ratio (SDNR) in the dual-energy recombined
image. The theoretical derivation of the iodine SDNR in the
recombined image allowed the prediction of the optimal low and
high-energy techniques. Depending on the breast thickness and
glandular percentage, the optimal low-energy kVp and mAs ranged from
24kVp (Mo/Mo or Mo/Rh) to 35kVp (Rh/Rh), and from 60 to 90mAs
respectively, and the high-energy kVp and mAs ranged from 40kVp to
47kVp (Mo/Cu), and from 80mAs to 290mAs. We proved the better
performance of our algorithm compared to the classic weighted
logarithmic subtraction method in terms of patient dose and also in terms of texture
cancelation, through the use of artificial textured images. Values of iodine contrast measured on phantom were
close to the expected iodine thickness. Good correlation was found
between the measured and theoretical iodine SDNR in the dual-energy
images, which validates our theoretical optimization of the
acquisition techniques.
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