Contrast-enhanced digital breast tomosynthesis (CEDBT) may improve contrast-enhanced lesion conspicuity and relative contrast quantification by improving three-dimensional visualization of lesion morphology, and reducing the integration of attenuation information along the axial direction. Improved visualization of patterns of contrast-enhancement and improved iodine quantification may help differentiate between malignant and benign enhancing lesions. The dependence of dual-energy contrast-enhanced lesion detectability on imaging chain design is investigated. Lesion detectability and relative iodine quantification is comparable for subtraction in either reconstruction or projection domains for both phantom and patient images. SART generally produces greater SDNR than FBP, and scatter correcting projections further improves SDNR.

1. DAVID A. SCADUTO1, YUE-HOUNG HU2, YIHUAN LU3, HAILIANG HUANG1, JINGXUAN LIU4, KIM RINALDI1,
GENE GINDI1, PAUL R. FISHER1, WEI ZHAO1
1Department of Radiology, Stony Brook Medicine, Stony Brook, New York 11794; 2Department of Radiation Oncology, Division of Medical Physics and Biophysics,
Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115; 3Departments of Radiology and Biomedical Engineering, Yale University,
New Haven, Connecticut 06520; 4Department of Pathology, Stony Brook Medicine, Stony Brook, New York 11794
Dependence of Contrast-Enhanced Lesion Detection in Contrast-
Enhanced Digital Breast Tomosynthesis on Imaging Chain Design
BACKGROUND
 Contrast-enhanced digital breast tomosynthesis (CEDBT) may
reduce false-positives compared with CE digital mammography
 Reduces contrast signal integration/superposition inherent to CEDM
 CEDBT may differentiate true/false positives, like DCE-MRI, through
o characterization of stippled/non-mass enhancement
o observation of contrast kinetics
 3D localization in CEDBT may differentiate non-mass enhancement
from background parenchymal enhancement
 Reducing contrast superposition may improve relative contrast
quantification
PURPOSE
 Investigate ability of CEDBT to
o identify small enhancements (stippled enhancement patterns)
o accurately quantify relative iodine concentration (contrast kinetics)
 Evaluate different imaging chain designs
METHODS
Experimental System
 Siemens MAMMOMAT Inspiration DBT system
 Modified for DE imaging
o Low Energy: W/Rh
o High Energy: W/Cu or W/Ti 49 kVp
o 300 μm a-Se detector
Phantom Imaging
 CIRS BR3D phantom
 Custom solid iodine insert
Patient Imaging
 IRB-approved clinical study
 Three patients, BI-RADS 4-5
 1.5-2.0 ml Omnipaque 350 per kg body weight
Imaging Chain Design
SDNR Analysis
 Measured for each iodine object concentration, diameter in phantom
for each imaging chain
o SDNR correlated to iodine concentration
 Measured in each patient for each imaging chain
RESULTS
Subtracted Reconstructions
 Six weighted subtractions produced for each dataset
 Weighting factor derived analytically and tuned empirically
RESULTS
SDNR Analysis
DISCUSSION
 Subtraction produces equivalent results in either projection or
reconstruction domains
 SART outperforms FBP, but judicious filter selection may improve
performance
 Scatter correcting projections improves SDNR for SART
 Strong correlation between iodine concentration and SDNR
 Future work: improve SDNR by further reducing residual structure
o Reduce misregistration due to patient motion
o Improve reconstruction, scatter correction algorithms
ACKNOWLEDGMENTS
We gratefully acknowledge financial support from NIH
(1 R01 CA148053 and 1 R01 EB002655) and Siemens
Healthcare.
2 mm 8 mm 2 mm 8 mm 2 mm 8 mm 2 mm 8 mm
1 mg/ml 2 mg/ml 3 mg/ml 5 mg/ml
0
2
4
6
8
10
Phantom Imaging
Subtraction Scheme
A1
A2
A3
B1
B2
B3
SDNR
Patient A Patient B Patient C
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Patient Imaging
SDNR
Subtraction Scheme
A1
A2
A3
B1
B2
B3
Fig. 4. SDNR of embedded iodine inserts in phantom and iodinated lesions in patient cases.
Subtraction in either domain gives essentially equivalent results. SART (A2-3/B2-3)
generally outperforms FBP. Scatter correcting before SART improves SDNR. Data from
Patient A could not be scatter corrected due to technical limitations of the algorithm.
Fig. 5. Measured SDNR of 8 mm iodine object
from phantom for each subtraction scheme.
Data were linearly fitted and Pearson
correlation coefficients calculated; r > 0.98 was
demonstrated for all cases. Subtraction
schemes in corresponding subtraction
domains (e.g., A1/B1) produced virtually
identical SDNR and thus appear to overlap.
Fig. 3. Single slices from subtracted (top) phantom reconstructions and (bottom) patient
reconstructions, according to imaging chain designs outlined in Fig. 2.
Fig. 1. (a) CIRS BR3D phantom with (b)
custom iodine insert.
Fig. 2. Imaging chain designs. Images subtracted in either reconstruction or projection
domain; reconstructed with FBP or SART; scatter corrected or uncorrected for SART.
0 1 2 3 4 5 6
-2
0
2
4
6
8
10
12 A1
r = 0.994
A2
r = 0.986
A3
r = 0.992
B1
r = 0.985
B2
r = 0.985
B3
r = 0.992
SDNR
Iodine Concentration (mg/ml)
LE/HE CEDBT Data
A1
A2
A3
B1
B2
B3
Reconstruction Domain
Subtraction
Projection Domain
Subtraction
SART
No Scatter Correction
Scatter Corrected
FBP No Scatter Correction
SART
No Scatter Correction
Scatter Corrected
FBP No Scatter Correction