Purpose

To design volume-specific breast phantoms from breast CT (bCT) data sets and estimate the associated normalized mean glandular dose coefficients for breast CT using Monte Carlo methods.

Methods

A large cohort of bCT data sets (N = 215) was used to evaluate breast volume into quintiles (plus the top 5%). The average radius profile was then determined for each of the six volume-specific groups and used to both fabricate physical phantoms and generate mathematical phantoms (V1-V6; "V" denotes classification by volume). The MCNP6 Monte Carlo code was used to model a prototype bCT system fabricated at our institution; and this model was validated against physical measurements in the fabricated phantoms. The mathematical phantoms were used to simulate normalized mean glandular dose coefficients for both monoenergetic source photons "DgN_CT (E)" (8-70 keV in 1 keV intervals) and polyenergetic x-ray beams "pDgN_CT " (35-70 kV in 1 kV intervals). The Monte Carlo code was used to study the influence of breast size (V1 vs. V5) and glandular fraction (6.4% vs. 45.8%) on glandular dose. The pDgN_CT coefficients estimated for the V1, V3, and V5 phantoms were also compared to those generated using simple, cylindrical phantoms with equivalent volume and two geometrical constraints including; (a) cylinder radius determined at the breast phantom chest wall "R_cw "; and (b) cylinder radius determined at the breast phantom center-of-mass "R_COM ".

Results

Satisfactory agreement was observed for dose estimations using MCNP6 compared with both physical measurements in the V1, V3, and V5 phantoms (R² = 0.995) and reference bCT dose coefficients using simple phantoms (R² = 0.999). For a 49 kV spectrum with 1.5 mm Al filtration, differences in glandular fraction [6.5% (5th percentile) vs. 45.8% (95th percentile)] had a 13.2% influence on pDgN_CT for the V3 phantom, and differences in breast size (V1 vs. V5) had a 16.6% influence on pDgN_CT for a breast composed of 17% (median) fibroglandular tissue. For cylindrical phantoms with a radius of R_COM , the differences were 1.5%, 0.1%, and 2.1% compared with the V1, V3, and V5 phantoms, respectively.

Conclusion

Breast phantoms were designed using a large cohort of bCT data sets across a range of six breast sizes. These phantoms were then fabricated and used for the estimation of glandular dose in breast CT. The mathematical phantoms and associated glandular dose coefficients for a range of breast sizes (V1-V6) and glandular fractions (5th to 95th percentiles) are available for interested users.

Purpose

Monte Carlo methods were used to generate lightly filtered high resolution x-ray spectra spanning from 20 kV to 640 kV.

Methods

X-ray spectra were simulated for a conventional tungsten anode. The Monte Carlo N-Particle eXtended radiation transport code (MCNPX 2.6.0) was used to produce 35 spectra over the tube potential range from 20 kV to 640 kV, and cubic spline interpolation procedures were used to create piecewise polynomials characterizing the photon fluence per energy bin as a function of x-ray tube potential. Using these basis spectra and the cubic spline interpolation, 621 spectra were generated at 1 kV intervals from 20 to 640 kV. The tungsten anode spectral model using interpolating cubic splines (TASMICS) produces minimally filtered (0.8 mm Be) x-ray spectra with 1 keV energy resolution. The TASMICS spectra were compared mathematically with other, previously reported spectra.

Results

Using pairedt-test analyses, no statistically significant difference (i.e., p > 0.05) was observed between compared spectra over energy bins above 1% of peak bremsstrahlung fluence. For all energy bins, the correlation of determination (R(2)) demonstrated good correlation for all spectral comparisons. The mean overall difference (MOD) and mean absolute difference (MAD) were computed over energy bins (above 1% of peak bremsstrahlung fluence) and over all the kV permutations compared. MOD and MAD comparisons with previously reported spectra were 2.7% and 9.7%, respectively (TASMIP), 0.1% and 12.0%, respectively [R. Birch and M. Marshall, "Computation of bremsstrahlung x-ray spectra and comparison with spectra measured with a Ge(Li) detector," Phys. Med. Biol. 24, 505-517 (1979)], 0.4% and 8.1%, respectively (Poludniowski), and 0.4% and 8.1%, respectively (AAPM TG 195). The effective energy of TASMICS spectra with 2.5 mm of added Al filtration ranged from 17 keV (at 20 kV) to 138 keV (at 640 kV); with 0.2 mm of added Cu filtration the effective energy was 9 keV at 20 kV and 169 keV at 640 kV.

Conclusions

Ranging from 20 kV to 640 kV, 621 x-ray spectra were produced and are available at 1 kV tube potential intervals. The spectra are tabulated at 1 keV intervals. TASMICS spectra were shown to be largely equivalent to published spectral models and are available in spreadsheet format for interested users by emailing the corresponding author (JMB).

The studies by Sahbaee et al were well performed, and the results are provocative, but the authors of this editorial suggest that there are limitations to all modeling studies and that the results should be considered as only the first chapter in a much longer story about the role of contrast agents on radiation dose at CT.

Conventional mammographic dosimetry has been developed over the past 40 years. Prior to the availability of high-resolution three-dimensional breast images, certain assumptions about breast anatomy were required. These assumptions were based on the information evident on two-dimensional mammograms; they included assumptions of thick skin, a uniform mixture of glandular and adipose tissue, and a median breast density of 50%. Recently, the availability of high-resolution breast CT studies has provided more accurate data about breast anatomy, and this, in turn, has provided the opportunity to update mammographic dosimetry. Based on hundreds of data sets on breast CT volume, a number of studies were performed and reported which have shed light on the basic breast anatomy specific to dosimetry in mammography. It was shown that the average skin thickness of the breast was approximately 1.5 mm, instead of the 4 or 5 mm in the past. In another study, 3-D breast CT data sets were used for validation of the 2-D algorithm developed at the University of Toronto, leading to data suggesting that the overall average breast density is of the order of 16-20%, rather than the previously assumed 50%. Both of these assumptions led to normalized glandular dose (DgN) coefficients which are higher than those of the past. However, a comprehensive study on hundreds of breast CT data sets confirmed the findings of other investigators that there is a more centralized average location of glandular tissue within the breast. Combined with Monte Carlo studies for dosimetry, when accurate models of the distribution of glandular tissue were used, a 30% reduction in the radiation dose (as determined by the DgN coefficient) was found as an average across typical molybdenum and tungsten spectra used clinically. The 30% average reduction was found even when the thinner skin and the lower average breast density were considered. The article reviews three specific anatomic observations made possible based on high-resolution breast CT data by several different research groups. It is noted that, periodically, previous assumptions pertaining to dosimetry can be updated when new information becomes available, so that more accurate dosimetry is achieved. Dogmatic practices typically change slowly, but it is hoped that the medical physics community will continue to evaluate changes in DgN coefficients such that they become more accurate.

Purpose

Current dosimetry methods in mammography assume that the breast is comprised of a homogeneous mixture of glandular and adipose tissues. Three-dimensional (3D) dedicated breast CT (bCT) data sets were used previously to assess the complex anatomical structure within the breast, characterizing the statistical distribution of glandular tissue in the breast. The purpose of this work was to investigate the effect of bCT-derived heterogeneous glandular distributions on dosimetry in mammography.

Methods

bCT-derived breast diameters, volumes, and 3D fibroglandular distributions were used to design realistic compressed breast models comprised of heterogeneous distributions of glandular tissue. The bCT-derived glandular distributions were fit to biGaussian functions and used as probability density maps to assign the density distributions within compressed breast models. The MCNPX 2.6.0 Monte Carlo code was used to estimate monoenergetic normalized mean glandular dose "DgN(E)" values in mammography geometry. The DgN(E) values were then weighted by typical mammography x-ray spectra to determine polyenergetic DgN (pDgN) coefficients for heterogeneous (pDgNhetero) and homogeneous (pDgNhomo) cases. The dependence of estimated pDgN values on phantom size, volumetric glandular fraction (VGF), x-ray technique factors, and location of the heterogeneous glandular distributions was investigated.

Results

The pDgNhetero coefficients were on average 35.3% (SD, 4.1) and 24.2% (SD, 3.0) lower than the pDgNhomo coefficients for the Mo-Mo and W-Rh x-ray spectra, respectively, across all phantom sizes and VGFs when the glandular distributions were centered within the breast phantom in the coronal plane. At constant breast size, increasing VGF from 7.3% to 19.1% lead to a reduction in pDgNhetero relative to pDgNhomo of 23.6%-27.4% for a W-Rh spectrum. Displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width in the superior and inferior directions, resulted in a 37.3% and a -26.6% change in the pDgNhetero coefficient, respectively, relative to the centered distribution for the Mo-Mo spectrum. Lateral displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width, resulted in a 1.5% change in the pDgNhetero coefficient relative to the centered distribution for the W-Rh spectrum.

Conclusions

Introducing bCT-derived heterogeneous glandular distributions into mammography phantom design resulted in decreased glandular dose relative to the widely used homogeneous assumption. A homogeneous distribution overestimates the amount of glandular tissue near the entrant surface of the breast, where dose deposition is exponentially higher. While these findings are based on clinically measured distributions of glandular tissue using a large cohort of women, future work is required to improve the classification of glandular distributions based on breast size and overall glandular fraction.

Purpose

Clinical use of dedicated breast computed tomography (bCT) requires relatively short scan times necessitating systems with high frame rates. This in turn impacts the x-ray tube operating range. We characterize the effects of tube voltage, beam filtration, dose, and object size on contrast and noise properties related to soft tissue and iodine contrast agents as a way to optimize imaging protocols for soft tissue and iodine contrast at high frame rates.

Methods

This study design uses the signal-difference-to-noise ratio (SDNR), noise-equivalent quanta (NEQ), and detectability (d´) as measures of imaging performance for a prototype breast CT scanner that utilizes a pulsed x-ray tube (with a 4 ms pulse width) at 43.5 fps acquisition rate. We assess a range of kV, filtration, breast phantom size, and mean glandular dose (MGD). Performance measures are estimated from images of adipose-equivalent breast phantoms machined to have a representative size and shape of small, medium, and large breasts. Water (glandular tissue equivalent) and iodine contrast (5 mg/ml) were used to fill two cylindrical wells in the phantoms.

Results

Air kerma levels required for obtaining an MGD of 6 mGy ranged from 7.1 to 9.1 mGy and are reported across all kV, filtration, and breast phantom sizes. However, at 50 kV, the thick filters (0.3 mm of Cu or Gd) exceeded the maximum available mA of the x-ray generator, and hence, these conditions were excluded from subsequent analysis. There was a strong positive association between measurements of SDNR and d' (R²  > 0.97) within the range of parameters investigated in this work. A significant decrease in soft tissue SDNR was observed for increasing phantom size and increasing kV with a maximum SDNR at 50 kV with 0.2 mm Cu or 0.2 mm Gd filtration. For iodine contrast SDNR, a significant decrease was observed with increasing phantom size, but a decrease in SDNR for increasing kV was only observed for 70 kV (50 and 60 kV were not significantly different). Thicker Gd filtration (0.3 mm Gd) resulted in a significant increase in iodine SDNR and decrease in soft tissue SDNR but requires significantly more tube current to deliver the same MGD.

Conclusions

The choice of 60 kV with 0.2 mm Gd filtration provides a good trade-off for maximizing both soft tissue and iodine contrast. This scanning technique takes advantage of the ~50 keV Gd k-edge to produce contrast and can be achieved within operating range of the x-ray generator used in this work. Imaging at 60 kV allows for a greater range in dose delivered to the large breast sizes when uniform image quality is desired across all breast sizes. While imaging performance metrics (i.e., detectability index and SDNR) were shown to be strongly correlated, the methodologies presented in this work for the estimation of NEQ (and subsequently d') provides a meaningful description of the spatial resolution and noise characteristics of this prototype bCT system across a range of beam quality, dose, and object sizes.

Purpose: To demonstrate the utility of high-resolution micro-computed tomography ( μ CT ) for determining ground-truth size and shape properties of calcium grains for evaluation of detection performance in breast CT (bCT). Approach: Calcium carbonate grains ( ∼ 200    μ m ) were suspended in 1% agar solution to emulate microcalcifications ( μ Calcs ) within a fibroglandular tissue background. Ground-truth imaging was performed on a commercial μ CT scanner and was used for assessing calcium-grain size and shape, and for generating μ Calc signal profiles. Calcium grains were placed within a realistic breast-shaped phantom and imaged on a prototype bCT system at 3- and 6-mGy mean glandular dose (MGD) levels, and the non-prewhitening detectability was assessed. Additionally, the μ CT -derived signal profiles were used in conjunction with the bCT system characterization (MTF and NPS) to obtain predictions of bCT detectability. Results: Estimated detectability of the calcium grains on the bCT system ranged from 2.5 to 10.6 for 3 mGy and from 3.8 to 15.3 for 6 mGy with large fractions of the grains meeting the Rose criterion for visibility. Segmentation of μ CT images based on morphological operations produced accurate results in terms of segmentation boundaries and segmented region size. A regression model linking bCT detectability to μ Calc parameters indicated significant effects of μ Calc size and vertical position within the breast phantom. Detectability using μ CT -derived detection templates and bCT statistical properties (MTF and NPS) were in good correspondence with those measured directly from bCT ( R 2 > 0.88 ). Conclusions: Parameters derived from μ CT ground-truth data were shown to produce useful characterizations of detectability when compared to estimates derived directly from bCT. Signal profiles derived from μ CT imaging can be used in conjunction with measured or hypothesized statistical properties to evaluate the performance of a system, or system component, that may not currently be available.

The design and testing of a prototype Multi-X-ray-source Array (MXA) for digital breast tomosynthesis is reported. The MXA is comprised of an array of tungsten filament cathodes with focus cup grid-controlled modulation and a common rotating anode housed in a single vacuum envelope. Prototypes consisting of arrays of three-source elements and eleven-source-elements were fabricated and evaluated. The prototype sources demonstrated focal spot sizes of 0.3 mm at 45 kV with 50 mA. Measured x-ray spectra were consistent with the molybdenum anode employed, and the tube output (air kerma) was between 0.6 mGy/100 mAs at 20 kV and 17 mGy/100 mAs at 45 kV with a distance of 100 cm. HVL measurements ranged from 0.5 mm Al at 30 kV to 0.8 mm Al at 45 kV, and x-ray pulse widths were varied from 20 ms to 110 ms at operating frequencies ultimately to be limited by source turn-on/off times of ∼1 ms. Initial results of reconstructed tomographic data are presented.

The purpose of this study was to compare various multisource configurations applied to cone beam CT (CBCT) using phantom imaging and Monte Carlo simulations. Image quality, scatter, and dose were evaluated in both overlapping (large cone angle) and collimated (small cone angle) configurations for CBCT. Four x-ray tube configurations were considered: traditional one source, three source overlapping, six source overlapping, and six source collimated. Image quality was evaluated on a prototype breast CT system using the following five phantoms: a Defrise phantom, a previously reported CBCT QA phantom (Corgi), a polyethylene cylinder, and two anthropomorphic phantoms (hand and knee). Scatter contamination and radiation dose were evaluated using Monte Carlo simulations of a voxelized polyethylene cylinder. The modulation of the Defrise phantom disks on average was 2.7X greater for the six source collimated configuration than the six source overlapping configuration. The data lost from cone beam artifact (spatial domain) and the null cone (frequency domain) in the overlapping configuration were completely recovered using the collimated configuration. The maximum scatter-to-primary ratio (SPR) for the overlapping configuration was 0.81 and the maximum SPR for the collimated configuration was 0.26. The average dose and maximum dose was 4X less in the collimated six source configuration when compared with the overlapping configurations. The maximum dose for the overlapping configurations (one, three & six) remained constant, but the average dose for the multisource (three & six source) overlapping configurations increased 25% when compared to the one source configuration. Use of a collimated multisource x-ray tube configuration was shown to provide significant improvements in image quality throughout the cone-beam geometry field-of-view, reduction in scatter contamination, and more efficient use of dose in comparison to both the traditional CBCT geometry with a single source and the overlapping multisource configurations.

Purpose

The purpose of this work was twofold: (a) To provide a robust and accurate method for image segmentation of dedicated breast CT (bCT) volume data sets, and (b) to improve Hounsfield unit (HU) accuracy in bCT by means of a postprocessing method that uses the segmented images to correct for the low-frequency shading artifacts in reconstructed images.

Methods

A sequential and iterative application of image segmentation and low-order polynomial fitting to bCT volume data sets was used in the interleaved correction (IC) method. Image segmentation was performed through a deep convolutional neural network (CNN) with a modified U-Net architecture. A total of 45 621 coronal bCT images from 111 patient volume data sets were segmented (using a previously published segmentation algorithm) and used for neural network training, validation, and testing. All patient data sets were selected from scans performed on four different prototype breast CT systems. The adipose voxels for each patient volume data set, segmented using the proposed CNN, were then fit to a three-dimensional low-order polynomial. The polynomial fit was subsequently used to correct for the shading artifacts introduced by scatter and beam hardening in a method termed "flat fielding." An interleaved utilization of image segmentation and flat fielding was repeated until a convergence criterion was satisfied. Mathematical and physical phantom studies were conducted to evaluate the dependence of the proposed algorithm on breast size and the distribution of fibroglandular tissue. In addition, a subset of patient scans (not used in the CNN training, testing or validation) were used to investigate the accuracy of the IC method across different scanner designs and beam qualities.

Results

The IC method resulted in an accurate classification of different tissue types with an average Dice similarity coefficient > 95%, precision > 97%, recall > 95%, and F1-score > 96% across all tissue types. The flat fielding correction of bCT images resulted in a significant reduction in either cupping or capping artifacts in both mathematical and physical phantom studies as measured by the integral nonuniformity metric with an average reduction of 71% for cupping and 30% for capping across different phantom sizes, and the Uniformity Index with an average reduction of 53% for cupping and 34% for capping.

Conclusion

The validation studies demonstrated that the IC method improves Hounsfield Units (HU) accuracy and effectively corrects for shading artifacts caused by scatter contamination and beam hardening. The postprocessing approach described herein is relevant to the broad scope of bCT devices and does not require any modification in hardware or existing scan protocols. The trained CNN parameters and network architecture are available for interested users.