Technique factors and their relationship to radiation dose in pendant geometry breast CT

Dedicated Breast CT: Getting Ready for Prime Time

Dedicated breast CT is an imaging modality that provides true 3D imaging of the breast with many advantages over current conventional breast imaging modalities. The addition of intravascular contrast increases the sensitivity of breast CT substantially. As such, there are immediate potential applications in the clinical workflow. These include using breast CT to replace much of the traditional diagnostic workup when faced with indeterminate breast lesions. Contrast-enhanced breast CT may be appropriate as a supplemental screening tool for women at high risk of breast cancer, similar to breast MRI. In addition, emerging studies are demonstrating the utility of breast CT in neoadjuvant chemotherapy tumor response monitoring as well as planning for surgical treatment options. While short exam times and fully 3D imaging in a noncompressed position are advantages of this modality, limited coverage of chest wall/axilla due to prone positioning and use of ionizing radiation are drawbacks. To date, several studies have reported on the performance characteristics of this promising modality.

Virtual dosimetry study with three cone-beam breast computed tomography scanners using a fast GPU-based Monte Carlo code

Objective. To compare the dosimetric performance of three cone-beam breast computed tomography (BCT) scanners, using real-time Monte Carlo-based dose estimates obtained with the virtual clinical trials (VCT)-BREAST graphical processing unit (GPU)-accelerated platform dedicated to VCT in breast imaging. Approach. A GPU-based Monte Carlo (MC) code was developed for replicatingin silicothe geometric, x-ray spectra and detector setups adopted, respectively, in two research scanners and one commercial BCT scanner, adopting 80 kV, 60 kV and 49 kV tube voltage, respectively. Our cohort of virtual breasts included 16 anthropomorphic voxelized breast phantoms from a publicly available dataset. For each virtual patient, we simulated exams on the three scanners, up to a nominal simulated mean glandular dose of 5 mGy (primary photons launched, in the order of 1011-1012per scan). Simulated 3D dose maps (recorded for skin, adipose and glandular tissues) were compared for the same phantom, on the three scanners. MC simulations were implemented on a single NVIDIA GeForce RTX 3090 graphics card.Main results.Using the spread of the dose distribution as a figure of merit, we showed that, in the investigated phantoms, the glandular dose is more uniform within less dense breasts, and it is more uniformly distributed for scans at 80 kV and 60 kV, than at 49 kV. A realistic virtual study of each breast phantom was completed in about 3.0 h with less than 1% statistical uncertainty, with 109primary photons processed in 3.6 s computing time.Significance. We reported the first dosimetric study of the VCT-BREAST platform, a fast MC simulation tool for real-time virtual dosimetry and imaging trials in BCT, investigating the dose delivery performance of three clinical BCT scanners. This tool can be adopted to investigate also the effects on the 3D dose distribution produced by changes in the geometrical and spectrum characteristics of a cone-beam BCT scanner.

Multiscale Monte Carlo simulations for dosimetry in x-ray breast imaging: Part I - Macroscopic scales

BACKGROUND

X-ray breast imaging modalities are commonly employed for breast cancer detection, from screening programs to diagnosis. Thus, dosimetry studies are important for quality control and risk estimation since ionizing radiation is used.

PURPOSE

To perform multiscale dosimetry assessments for different breast imaging modalities and for a variety of breast sizes and compositions. The first part of our study is focused on macroscopic scales (down to millimeters).

METHODS

Nine anthropomorphic breast phantoms with a voxel resolution of 0.5 mm were computationally generated using the BreastPhantom software, representing three breast sizes with three distinct values of volume glandular fraction (VGF) for each size. Four breast imaging modalities were studied: digital mammography (DM), contrast-enhanced digital mammography (CEDM), digital breast tomosynthesis (DBT) and dedicated breast computed tomography (BCT). Additionally, the impact of tissue elemental compositions from two databases were compared. Monte Carlo (MC) simulations were performed with the MC-GPU code to obtain the 3D glandular dose distribution (GDD) for each case considered with the mean glandular dose (MGD) fixed at 4 mGy (to facilitate comparisons).

RESULTS

The GDD within the breast is more uniform for CEDM and BCT compared to DM and DBT. For large breasts and high VGF, the ratio between the minimum/maximum glandular dose to MGD is 0.12/4.02 for DM and 0.46/1.77 for BCT; the corresponding results for a small breast and low VGF are 0.35/1.98 (DM) and 0.63/1.42 (BCT). The elemental compositions of skin, adipose and glandular tissue have a considerable impact on the MGD, with variations up to 30% compared to the baseline. The inclusion of tissues other than glandular and adipose within the breast has a minor impact on MGD, with differences below 2%. Variations in the final compressed breast thickness alter the shape of the GDD, with a higher compression resulting in a more uniform GDD.

CONCLUSIONS

For a constant MGD, the GDD varies with imaging modality and breast compression. Elemental tissue compositions are an important factor for obtaining MGD values, being a source of systematic uncertainties in MC simulations and, consequently, in breast dosimetry.

Convolutional neural network-based model observer for signal known statistically task in breast tomosynthesis images

BACKGROUND

Since human observer studies are resource-intensive, mathematical model observers are frequently used to assess task-based image quality. The most common implementation of these model observers assume that the signal information is exactly known. However, these tasks cannot thoroughly represent situations where the signal information is not exactly known in terms of size and shape.

PURPOSE

Considering the limitations of the tasks for which signal information is exactly known, we proposed a convolutional neural network (CNN)-based model observer for signal known statistically (SKS) and background known statistically (BKS) detection tasks in breast tomosynthesis images.

METHODS

A wide parameter search was conducted from six different acquisition angles (i.e., 10°, 20°, 30°, 40°, 50°, and 60°) within the same dose level (i.e., 2.3 mGy) under two separate acquisition schemes: (1) constant total number of projections, and (2) constant angular separation between projections. Two different types of signals: spherical (i.e., SKE tasks) and spiculated (i.e., SKS tasks) were used. The detection performance of the CNN-based model observer was compared with that of the Hotelling observer (HO) instead of the IO. Pixel-wise gradient-weighted class activation mapping (pGrad-CAM) map was extracted from each reconstructed tomosynthesis image to provide an intuitive understanding of the trained CNN-based model observer.

RESULTS

The CNN-based model observer achieved a higher detection performance compared to that of the HO for all tasks. Moreover, the improvement in its detection performance was greater for SKS tasks compared to that for SKE tasks. These results demonstrated that the addition of nonlinearity improved the detection performance owing to the variation of the background and signal. Interestingly, the pGrad-CAM results effectively localized the class-specific discriminative region, further supporting the quantitative evaluation results of the CNN-based model observer. In addition, we verified that the CNN-based model observer required fewer images to achieve the detection performance of the HO.

CONCLUSIONS

In this work, we proposed a CNN-based model observer for SKS and BKS detection tasks in breast tomosynthesis images. Throughout the study, we demonstrated that the detection performance of the proposed CNN-based model observer was superior to that of the HO.

Effect of optical blurring of X-ray source on breast tomosynthesis image quality: Modulation transfer function, anatomical noise power spectrum, and signal detectability perspectives

We investigated the effect of the optical blurring of X-ray source on digital breast tomosynthesis (DBT) image quality using well-designed DBT simulator and table-top experimental systems. To measure the in-plane modulation transfer function (MTF), we used simulated sphere phantom and Teflon sphere phantom and generated their projection data using two acquisition modes (i.e., step-and-shoot mode and continuous mode). After reconstruction, we measured the in-plane MTF using reconstructed sphere phantom images. In addition, we measured the anatomical noise power spectrum (aNPS) and signal detectability. We constructed simulated breast phantoms with a 50% volume glandular fraction (VGF) of breast anatomy using the power law spectrum and inserted spherical objects with 1 mm, 2 mm, and 5 mm diameters as breast masses. Projection data were acquired using two acquisition modes, and in-plane breast images were reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm. For the experimental study, we used BR3D breast phantom with 50% VGF and obtained projection data using a table-top experimental system. To compare the detection performance of the two acquisition modes, we calculated the signal detectability using the channelized Hotelling observer (CHO) with Laguerre-Gauss (LG) channels. Our results show that spatial resolution of in-plane image in continuous mode was degraded due to the optical blurring of X-ray source. This blurring effect was reflected in aNPS, resulting in large β values. From a signal detectability perspective, the signal detectability in step-and-shoot mode is higher than that in continuous mode for small spherical signals but not large spherical signals. Although the step-and-shoot mode has disadvantage in terms of scan time compared to the continuous mode, scanning in step-and-shoot mode is better for detecting small signals, indicating that there is a tradeoff between scan time and image quality.

Comparisons of glandular breast dose between digital mammography, tomosynthesis and breast CT based on anthropomorphic patient-derived breast phantoms

PURPOSE

To evaluate the bias to the mean glandular dose (MGD) estimates introduced by the homogeneous breast models in digital breast tomosynthesis (DBT) and to have an insight into the glandular dose distributions in 2D (digital mammography, DM) and 3D (DBT and breast dedicated CT, BCT) x-ray breast imaging by employing breast models with realistic glandular tissue distribution and organ silhouette.

METHODS

A Monte Carlo software for DM, DBT and BCT simulations was adopted for the evaluation of glandular dose distribution in 60 computational anthropomorphic phantoms. These computational phantoms were derived from 3D breast images acquired via a clinical BCT scanner.

RESULTS

g·c·s·T conversion coefficients based on homogeneous breast model led to a MGD overestimate of 18% in DBT when compared to MGD estimated via anthropomorphic phantoms; this overestimate increased up to 21% for recently computed DgN_DBT conversion coefficients. The standard deviation of the glandular dose distribution in BCT resulted 60% lower than in DM and 55% lower than in DBT. The glandular dose peak - evaluated as the average value over the 5% of the gland receiving the highest dose - is 2.8 times the MGD in DM, this factor reducing to 2.6 and 1.6 in DBT and BCT, respectively.

CONCLUSIONS

Conventional conversion coefficients for MGD estimates based on homogeneous breast models overestimate MGD by 18%, when compared to MGD estimated via anthropomorphic phantoms. The ratio between the peak glandular dose and the MGD is 2.8 in DM. This ratio is 8% and 75% higher than in DBT and BCT, respectively.

Dedicated breast CT: state of the art-Part I. Historical evolution and technical aspects

Dedicated breast CT is an emerging 3D isotropic imaging technology for breast, which overcomes the limitations of 2D compression mammography and limited angle tomosynthesis while providing some of the advantages of magnetic resonance imaging. This first installment in a 2-part review describes the evolution of dedicated breast CT beginning with a historical perspective and progressing to the present day. Moreover, it provides an overview of state-of-the-art technology. Particular emphasis is placed on technical limitations in scan protocol, radiation dose, breast coverage, patient comfort, and image artifact. Proposed methods of how to address these technical challenges are also discussed. KEY POINTS: • Advantages of breast CT include no tissue overlap, improved patient comfort, rapid acquisition, and concurrent assessment of microcalcifications and contrast enhancement. • Current clinical and prototype dedicated breast CT systems differ in acquisition modes, imaging techniques, and detector types. • There are still details to be decided regarding breast CT techniques, such as scan protocol, radiation dose, breast coverage, patient comfort, and image artifact.

A signal detection model for quantifying overregularization in nonlinear image reconstruction

Many useful image quality metrics for evaluating linear image reconstruction techniques do not apply to or are difficult to interpret for nonlinear image reconstruction. The vast majority of metrics employed for evaluating nonlinear image reconstruction are based on some form of global image fidelity, such as image root mean square error (RMSE). Use of such metrics can lead to overregularization in the sense that they can favor removal of subtle details in the image. To address this shortcoming, we develop an image quality metric based on signal detection that serves as a surrogate to the qualitative loss of fine image details. The metric is demonstrated in the context of a breast CT simulation, where different equal-dose configurations are considered. The configurations differ in the number of projections acquired. Image reconstruction is performed with a nonlinear algorithm based on total variation constrained least-squares (TV-LSQ). The resulting images are studied as a function of three parameters: number of views acquired, total variation constraint value, and number of iterations. The images are evaluated visually, with image RMSE, and with the proposed signal-detection-based metric. The latter uses a small signal, and computes detectability in the sinogram and in the reconstructed image. Loss of signal detectability through the image reconstruction process is taken as a quantitative measure of loss of fine details in the image. Loss of signal detectability is seen to correlate well with the blocky or patchy appearance due to overregularization with TV-LSQ, and this trend runs counter to the image RMSE metric, which tends to favor the over-regularized images. The proposed signal detection-based metric provides an image quality assessment that is complimentary to that of image RMSE. Using the two metrics in concert may yield a useful prescription for determining CT algorithm and configuration parameters when nonlinear image reconstruction is used.

Radiation dosimetry of a clinical prototype dedicated cone-beam breast CT system with offset detector

PURPOSE

A clinical-prototype, dedicated, cone-beam breast computed tomography (CBBCT) system with offset detector is undergoing clinical evaluation at our institution. This study is to estimate the normalized glandular dose coefficients ( DgN CT ) that provide air kerma-to-mean glandular dose conversion factors using Monte Carlo simulations.

MATERIALS AND METHODS

The clinical prototype CBBCT system uses 49 kV x-ray spectrum with 1.39 mm 1st half-value layer thickness. Monte Carlo simulations (GATE, version 8) were performed with semi-ellipsoidal, homogeneous breasts of various fibroglandular weight fractions ( f g = 0.01 , 0.15 , 0.5 , 1 ) , chest wall diameters ( d = 8 , 10 , 14 , 18 , 20  cm), and chest wall to nipple length ( l = 0.75 d ), aligned with the axis of rotation (AOR) located at 65 cm from the focal spot to determine the DgN CT . Three geometries were considered - 40 × 30 -cm detector with no offset that served as reference and corresponds to a clinical CBBCT system, 30 × 30 -cm detector with 5 cm offset, and a 30 × 30 -cm detector with 10 cm offset.

RESULTS

For 5 cm lateral offset, the DgN CT ranged 0.177 - 0.574  mGy/mGy and reduction in DgN CT with respect to reference geometry was observed only for 18 cm ( 6.4 % ± 0.23 % ) and 20 cm ( 9.6 % ± 0.22 % ) diameter breasts. For the 10 cm lateral offset, the DgN CT ranged 0.221 - 0.581  mGy/mGy and reduction in DgN CT was observed for all breast diameters. The reduction in DgN CT was 1.4 % ± 0.48 % , 7.1 % ± 0.13 % , 17.5 % ± 0.19 % , 25.1 % ± 0.15 % , and 27.7 % ± 0.08 % for 8, 10, 14, 18, and 20 cm diameter breasts, respectively. For a given breast diameter, the reduction in DgN CT with offset-detector geometries was not dependent on f g . Numerical fits of DgN CT d , l , f g were generated for each geometry.

CONCLUSION

The DgN CT and the numerical fit, D g N CT d , l , f g would be of benefit for current CBBCT systems using the reference geometry and for future generations using offset-detector geometry. There exists a potential for radiation dose reduction with offset-detector geometry, provided the same technique factors as the reference geometry are used, and the image quality is clinically acceptable.

Experimental optimization of the energy for breast-CT with synchrotron radiation

Breast Computed Tomography (bCT) is a three-dimensional imaging technique that is raising interest among radiologists as a viable alternative to mammographic planar imaging. In X-rays imaging it would be desirable to maximize the capability of discriminating different tissues, described by the Contrast to Noise Ratio (CNR), while minimizing the dose (i.e. the radiological risk). Both dose and CNR are functions of the X-ray energy. This work aims at experimentally investigating the optimal energy that, at fixed dose, maximizes the CNR between glandular and adipose tissues. Acquisitions of both tissue-equivalent phantoms and actual breast specimens have been performed with the bCT system implemented within the Syrma-3D collaboration at the Syrmep beamline of the Elettra synchrotron (Trieste). The experimental data have been also compared with analytical simulations and the results are in agreement. The CNR is maximized at energies around 26–28 keV. These results are in line with the outcomes of a previously presented simulation study which determined an optimal energy of 28 keV for a large set of breast phantoms with different diameters and glandular fractions. Finally, a study on photon starvation has been carried out to investigate how far the dose can be reduced still having suitable images for diagnostics.

Novel imaging approaches to screen for breast cancer: Recent advances and future prospects

AIM OF THE STUDY

Over the past 50 years, the application of mammography - an X-ray of the breast - to screen healthy women has been a successful strategy to reduce breast cancer mortality. The aim of this study was to review the literature on novel imaging approaches that have the potential to replace mammography.

METHODS

An online literature search was carried out using PubMed, Google Scholar, ScienceDirect and Google Patents. The search keywords included "breast cancer", "imaging" and "screening", with 51 journal articles and five United States patents being selected for review. Seventeen relevant online sources were also identified and referenced.

RESULTS

In addition to full-field digital mammography (FFDM), a further nine imaging modalities were identified for review. These included: digital breast tomosynthesis (DBT); breast computed tomography (BCT); automated breast ultrasound (ABUS); fusion of FFDM and ABUS; fusion of DBT and ABUS; magnetic resonance imaging (MRI); optical imaging; radio-wave imaging; and tactile sensor imaging. Important parameters were considered: diagnostic success (sensitivity and specificity), especially in dense breasts; time to acquire the images; and capital cost of the equipment.

CONCLUSIONS

DBT is rapidly replacing FFDM although it still misses invasive cancers in dense tissue. The fusion of ABUS, either with FFDM or DBT, will lead to sensitivity and specificity approaching 100%. The fusion of opto-acoustic imaging with ultrasound holds considerable promise for the future.

Optimization of the energy for Breast monochromatic absorption X-ray Computed Tomography

The limits of mammography have led to an increasing interest on possible alternatives such as the breast Computed Tomography (bCT). The common goal of all X-ray imaging techniques is to achieve the optimal contrast resolution, measured through the Contrast to Noise Ratio (CNR), while minimizing the radiological risks, quantified by the dose. Both dose and CNR depend on the energy and the intensity of the X-rays employed for the specific imaging technique. Some attempts to determine an optimal energy for bCT have suggested the range 22 keV-34 keV, some others instead suggested the range 50 keV-60 keV depending on the parameters considered in the study. Recent experimental works, based on the use of monochromatic radiation and breast specimens, show that energies around 32 keV give better image quality respect to setups based on higher energies. In this paper we report a systematic study aiming at defining the range of energies that maximizes the CNR at fixed dose in bCT. The study evaluates several compositions and diameters of the breast and includes various reconstruction algorithms as well as different dose levels. The results show that a good compromise between CNR and dose is obtained using energies around 28 keV.

Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach

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.

Conspicuity of suspicious breast lesions on contrast enhanced breast CT compared to digital breast tomosynthesis and mammography

OBJECTIVE

Compare conspicuity of suspicious breast lesions on contrast-enhanced dedicated breast CT (CEbCT), tomosynthesis (DBT) and digital mammography (DM).

METHODS

100 females with BI-RADS 4/5 lesions underwent CEbCT and/or DBT prior to biopsy in this IRB approved, HIPAA compliant study. Two breast radiologists adjudicated lesion conspicuity scores (CS) for each modality independently. Data are shown as mean CS ±standard deviation. Two-sided t-test was used to determine significance between two modalities within each subgroup. Multiple comparisons were controlled by the false-discovery rate set to 5%.

RESULTS

50% of studied lesions were biopsy-confirmed malignancies. Malignant masses were more conspicuous on CEbCT than on DBT or DM (9.7 ±0.5, n = 25; 6.8 ± 3.1, n = 15; 6.7 ± 3.0, n = 27; p < 0.05). Malignant calcifications were equally conspicuous on all three modalities (CEbCT 8.7 ± 0.8, n = 18; DBT 8.5 ± 0.6, n = 15; DM 8.8 ± 0.7, n = 23; p = NS). Benign masses were equally conspicuous on CEbCT (6.6 ± 4.1, n = 22); DBT (6.4 ± 3.8, n = 17); DM (5.9 ± 3.6, n = 24; p = NS). Benign calcifications CS were similar between DBT (8.5 ± 1.0, n = 17) and DM (8.8 ± 0.8, n = 26; p = NS) but less conspicuous on CEbCT (4.0 ± 2.9, n = 25, p < 0.001). 55 females were imaged with all modalities. Results paralleled the entire cohort. 69%(n = 62) of females imaged by CEbCT had dense breasts. Benign/malignant lesion CSs in dense/non-dense categories were 4.8 ± 3.7, n = 33, vs 6.0 ± 3.9, n = 14, p = 0.35; 9.2 ± 0.9, n = 29 vs. 9.4 ± 0.7, n = 14; p = 0.29, respectively.

CONCLUSION

Malignant masses are more conspicuous on CEbCT than DM or DBT. Malignant microcalcifications are equally conspicuous on all three modalities. Benign calcifications remain better visualized by DM and DBT than with CEbCT. We observed no differences in benign masses on all modalities. CS of both benign and malignant lesions were independent of breast density.

ADVANCES IN KNOWLEDGE

CEbCT is a promising diagnostic imaging modality for suspicious breast lesions.

Monochromatic breast computed tomography with synchrotron radiation: phase-contrast and phase-retrieved image comparison and full-volume reconstruction

A program devoted to performing the first in vivo synchrotron radiation (SR) breast computed tomography (BCT) is ongoing at the Elettra facility. Using the high spatial coherence of SR, phase-contrast (PhC) imaging techniques can be used. The latest high-resolution BCT acquisitions of breast specimens, obtained with the propagation-based PhC approach, are herein presented as part of the SYRMA-3D collaboration effort toward the clinical exam. Images are acquired with a 60 - μ m   pixel dead-time-free single-photon-counting CdTe detector. The samples are imaged at 32 and 38 keV in a continuous rotating mode, delivering 5 to 20 mGy of mean glandular dose. Contrast-to-noise ratio (CNR) and spatial resolution performances are evaluated for both PhC and phase-retrieved images, showing that by applying the phase-retrieval algorithm a five-time CNR increase can be obtained with a minor loss in spatial resolution across soft tissue interfaces. It is shown that, despite having a poorer CNR, PhC images can provide a sharper visualization of microcalcifications, thus being complementary to phase-retrieved images. Furthermore, the first full-volume scan of a mastectomy sample ( 9 × 9 × 3    cm 3 ) is reported. This investigation into surgical specimens indicates that SR BCT in terms of CNR, spatial resolution, scan duration, and scan volume is feasible.

Evaluation of human observer performance on lesion detectability in single-slice and multislice dedicated breast cone beam CT images with breast anatomical background

PURPOSE

We evaluate the lesion detectability using human and model observer studies in single-slice and multislice cone beam computed tomography (CBCT) images with a breast anatomical background. The purposes of this work are (a) to compare human observer detectability between single-slice and multislice images for different signal sizes and noise structures, (b) to investigate the effect of different multislice viewing modes (i.e., sequential and simultaneous) on the detectability by a human observer, and (c) to predict the detectability by a human observer in single-slice and multislice images using single-slice channelized Hotelling observer (ssCHO) and multislice CHO (msCHO), respectively.

METHODS

Breast anatomical background is modeled using a power law spectrum of mammograms and the lesion is modeled with a spherical signal. We conduct signal-known-exactly and background-known-statistically detection tasks on transverse and longitudinal images reconstructed using the Feldkamp-Davis-Kress algorithm with Hanning and Ram-Lak weighted ramp filters. The human observer study is conducted on three different viewing modes: single-slice, and sequential and simultaneous multislice. To predict the detectability by a human observer, we use ssCHO and msCHO with anthropomorphic channels (i.e., dense difference-of-Gaussian (D-DOG) and Gabor channels) and internal noise.

RESULTS

The detectability by a human observer increases for multislice images compared to single-slice images. For multislice images, the sequential viewing mode yields higher detectability than the simultaneous viewing mode. However, the relative rank of detectability by a human observer for different signal sizes, image planes, and reconstruction filters is not much different between the viewing modes. Detectability by CHO with internal noise shows good correlation with that of the human observer for all viewing modes.

CONCLUSIONS

Detectability by a human observer in CBCT images with breast anatomical background is affected by the image viewing mode, and the effect of the viewing mode depends on the signal size and noise structure. D-DOG and Gabor CHO with internal noise predict the detectability by a human observer well for both the single-slice and multislice image viewing modes.

Human and model observer performance for lesion detection in breast cone beam CT images with the FDK reconstruction

We investigate the detectability of breast cone beam computed tomography images using human and model observers and the variations of exponent, β, of the inverse power-law spectrum for various reconstruction filters and interpolation methods in the Feldkamp-Davis-Kress (FDK) reconstruction. Using computer simulation, a breast volume with a 50% volume glandular fraction and a 2mm diameter lesion are generated and projection data are acquired. In the FDK reconstruction, projection data are apodized using one of three reconstruction filters; Hanning, Shepp-Logan, or Ram-Lak, and back-projection is performed with and without Fourier interpolation. We conduct signal-known-exactly and background-known-statistically detection tasks. Detectability is evaluated by human observers and their performance is compared with anthropomorphic model observers (a non-prewhitening observer with eye filter (NPWE) and a channelized Hotelling observer with either Gabor channels or dense difference-of-Gaussian channels). Our results show that the NPWE observer with a peak frequency of 7cyc/degree attains the best correlation with human observers for the various reconstruction filters and interpolation methods. We also discover that breast images with smaller β do not yield higher detectability in the presence of quantum noise.

Modelling the transport of optical photons in scintillation detectors for diagnostic and radiotherapy imaging

Computational modelling of radiation transport can enhance the understanding of the relative importance of individual processes involved in imaging systems. Modelling is a powerful tool for improving detector designs in ways that are impractical or impossible to achieve through experimental measurements. Modelling of light transport in scintillation detectors used in radiology and radiotherapy imaging that rely on the detection of visible light plays an increasingly important role in detector design. Historically, researchers have invested heavily in modelling the transport of ionizing radiation while light transport is often ignored or coarsely modelled. Due to the complexity of existing light transport simulation tools and the breadth of custom codes developed by users, light transport studies are seldom fully exploited and have not reached their full potential. This topical review aims at providing an overview of the methods employed in freely available and other described optical Monte Carlo packages and analytical models and discussing their respective advantages and limitations. In particular, applications of optical transport modelling in nuclear medicine, diagnostic and radiotherapy imaging are described. A discussion on the evolution of these modelling tools into future developments and applications is presented.

Evaluation of Dose Homogeneity in Cone-Beam Breast Computed Tomography

The aim of this study is to determine, via measurements on phantoms and Monte Carlo (MC) simulations, the dose distribution of absorbed dose in a cone-beam breast computed tomography scan. The absorbed dose volume distribution was measured inside a polyethylene cylindrical phantom, simulating adipose breast tissue, using LiF:Mg,Ti thermoluminescence dosimeters. A reasonable agreement (between 2 and 8%) between the simulated and measured data was observed. The 3D distribution of absorbed dose was evaluated at 40, 60 and 80 kV in a phantom simulating a pendant breast. MC simulations indicate a significantly lower spread of volume dose than in mammography. The dose variation along the radial distance in the simulated phantoms was in the range of 4‒14%. These findings might be useful when devising models for breast imaging dose assessment that take into account the uneven distribution of the glandular mass in the breast volume.

Evaluation of the BreastSimulator software platform for breast tomography

The aim of this work was the evaluation of the software BreastSimulator, a breast x-ray imaging simulation software, as a tool for the creation of 3D uncompressed breast digital models and for the simulation and the optimization of computed tomography (CT) scanners dedicated to the breast. Eight 3D digital breast phantoms were created with glandular fractions in the range 10%-35%. The models are characterised by different sizes and modelled realistic anatomical features. X-ray CT projections were simulated for a dedicated cone-beam CT scanner and reconstructed with the FDK algorithm. X-ray projection images were simulated for 5 mono-energetic (27, 32, 35, 43 and 51 keV) and 3 poly-energetic x-ray spectra typically employed in current CT scanners dedicated to the breast (49, 60, or 80 kVp). Clinical CT images acquired from two different clinical breast CT scanners were used for comparison purposes. The quantitative evaluation included calculation of the power-law exponent, β, from simulated and real breast tomograms, based on the power spectrum fitted with a function of the spatial frequency, f, of the form S(f)  =  α/f   ^β . The breast models were validated by comparison against clinical breast CT and published data. We found that the calculated β coefficients were close to that of clinical CT data from a dedicated breast CT scanner and reported data in the literature. In evaluating the software package BreastSimulator to generate breast models suitable for use with breast CT imaging, we found that the breast phantoms produced with the software tool can reproduce the anatomical structure of real breasts, as evaluated by calculating the β exponent from the power spectral analysis of simulated images. As such, this research tool might contribute considerably to the further development, testing and optimisation of breast CT imaging techniques.

Investigation of x-ray spectra for iodinated contrast-enhanced dedicated breast CT

Screening for breast cancer with mammography has been very successful, resulting in part to a reduction of breast cancer mortality by approximately 39% since 1990. However, mammography still has limitations in performance, especially for women with dense breast tissue. Iodinated contrast-enhanced, dedicated breast CT (BCT) has been proposed to improve lesion analysis and the accuracy of diagnostic workup for patients suspected of having breast cancer. A mathematical analysis to explore the use of various x-ray filters for iodinated contrast-enhanced BCT is presented. To assess task-based performance, the ideal linear observer signal-to-noise ratio (SNR) is used as a figure-of-merit under the assumptions of a linear, shift-invariant imaging system. To estimate signal and noise propagation through the BCT detector, a parallel-cascade model was used. The lesion model was embedded into a structured background and included a realistic level of iodine uptake. SNR was computed for 84,000 different exposure settings by varying the kV setting, x-ray filter materials and thickness, breast size, and composition and radiation dose. It is shown that some x-ray filter material/thickness combinations can provide up to 75% improvement in the linear ideal observer SNR over a conventionally used x-ray filter for BCT. This improvement in SNR can be traded off for substantial reductions in mean glandular dose.

Review of clinical studies and first clinical experiences with a commercially available cone-beam breast CT in Europe

The dedicated cone-beam breast computed tomography (CBBCT) is a new and promising imaging modality which provides isotropic, 3D images of the breast with high spatial and contrast resolution. Non-contrast and contrast-enhanced CBBCT (CE-CBBCT) was superior to mammography for the visualization of breast masses, especially in patients with dense breast tissue. CE-CBBCT accurately detects DCIS and distinguishes it from benign causes of microcalcifications when compared with non-contrast CBBCT and mammography. The purpose of this report is to describe the technology and its possible indications, and to present the first results from recent clinical studies, illustrating these with our own image examples.

Dosimetry in x-ray-based breast imaging

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable.

Quantification of breast lesion compositions using low-dose spectral mammography: A feasibility study

PURPOSE

The positive predictive power for malignancy can potentially be improved, if the chemical compositions of suspicious breast lesions can be reliably measured in screening mammography. The purpose of this study is to investigate the feasibility of quantifying breast lesion composition, in terms of water and lipid contents, with spectral mammography.

METHODS

Phantom and tissue samples were imaged with a spectral mammography system based on silicon-strip photon-counting detectors. Dual-energy calibration was performed for material decomposition, using plastic water and adipose-equivalent phantoms as the basis materials. The step wedge calibration phantom consisted of 20 calibration configurations, which ranged from 2 to 8 cm in thickness and from 0% to 100% in plastic water density. A nonlinear rational fitting function was used in dual-energy calibration of the imaging system. Breast lesion phantoms, made from various combinations of plastic water and adipose-equivalent disks, were embedded in a breast mammography phantom with a heterogeneous background pattern. Lesion phantoms with water densities ranging from 0% to 100% were placed at different locations of the heterogeneous background phantom. The water density in the lesion phantoms was measured using dual-energy material decomposition. The thickness and density of the background phantom were varied to test the accuracy of the decomposition technique in different configurations. In addition, an in vitro study was also performed using mixtures of lean and fat bovine tissue of 25%, 50%, and 80% lean weight percentages as the background. Lesions were simulated by using breast lesion phantoms, as well as small bovine tissue samples, composed of carefully weighed lean and fat bovine tissues. The water densities in tissue samples were measured using spectral mammography and compared to measurement using chemical decomposition of the tissue.

RESULTS

The thickness of measured and known water contents was compared for various lesion configurations. There was a good linear correlation between the measured and the known values. The root-mean-square errors in water thickness measurements were 0.3 and 0.2 mm for the plastic phantom and bovine tissue backgrounds, respectively.

CONCLUSIONS

The results indicate that spectral mammography can be used to accurately characterize breast lesion composition in terms of their equivalent water and lipid contents.

Towards breast tomography with synchrotron radiation at Elettra: first images

The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 μm)(3) CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR.

X-ray scatter correction method for dedicated breast computed tomography: improvements and initial patient testing

A previously proposed x-ray scatter correction method for dedicated breast computed tomography was further developed and implemented so as to allow for initial patient testing. The method involves the acquisition of a complete second set of breast CT projections covering 360° with a perforated tungsten plate in the path of the x-ray beam. To make patient testing feasible, a wirelessly controlled electronic positioner for the tungsten plate was designed and added to a breast CT system. Other improvements to the algorithm were implemented, including automated exclusion of non-valid primary estimate points and the use of a different approximation method to estimate the full scatter signal. To evaluate the effectiveness of the algorithm, evaluation of the resulting image quality was performed with a breast phantom and with nine patient images. The improvements in the algorithm resulted in the avoidance of introduction of artifacts, especially at the object borders, which was an issue in the previous implementation in some cases. Both contrast, in terms of signal difference and signal difference-to-noise ratio were improved with the proposed method, as opposed to with the correction algorithm incorporated in the system, which does not recover contrast. Patient image evaluation also showed enhanced contrast, better cupping correction, and more consistent voxel values for the different tissues. The algorithm also reduces artifacts present in reconstructions of non-regularly shaped breasts. With the implemented hardware and software improvements, the proposed method can be reliably used during patient breast CT imaging, resulting in improvement of image quality, no introduction of artifacts, and in some cases reduction of artifacts already present. The impact of the algorithm on actual clinical performance for detection, diagnosis and other clinical tasks in breast imaging remains to be evaluated.

The utility of breast cone-beam computed tomography, ultrasound, and digital mammography for detecting malignant breast tumors: A prospective study with 212 patients

PURPOSE

Breast cone-beam computed tomography (BCBCT) is a flat-panel detector (FPD)-based X-ray imaging system that provides high-quality images of the breast. The purpose of this study was to investigate the ability to detect breast abnormalities using non-contrast BCBCT and contrast-enhanced BCBCT (BCBCT and CE-BCBCT) compared to ultrasound (US) and digital mammography (MG).

MATERIALS AND METHODS

A prospective study was performed from May 2012 to August 2014. Ninety-two patients (172 lesions) underwent BCBCT alone, and 120 patients (270 lesions) underwent BCBCT and CE-BCBCT, all the patients underwent US and MG.

RESULTS

Cancer diagnosis was confirmed pathologically in 102 patients (110 lesions). BCBCT identified 97 of 110 malignant lesions, whereas 93 malignant lesions were identified using MG and US. The areas under the receiver operating curves (AUCs) for breast cancer diagnosis were 0.861 (BCBCT), 0.856 (US), and 0.829 (MG). CE-BCBCT improved cancer diagnostic sensitivity by 20.3% (78.4-98.7%). The AUC values were 0.869 (CE-BCBCT), 0.846 (BCBCT), 0.834 (US), and 0.782 (MG).

CONCLUSION

In this preliminary study, BCBCT was found to accurately identify malignant breast lesions in a diagnostic setting. CE-BCBCT provided additional information and improved cancer diagnosis in style c or d breasts compared to the use of BCBCT, US, or MG alone.

Mean glandular dose coefficients (D(g)N) for x-ray spectra used in contemporary breast imaging systems

To develop tables of normalized glandular dose coefficients D(g)N for a range of anode-filter combinations and tube voltages used in contemporary breast imaging systems. Previously published mono-energetic D(g)N values were used with various spectra to mathematically compute D(g)N coefficients. The tungsten anode spectra from TASMICS were used; molybdenum and rhodium anode-spectra were generated using MCNPX Monte Carlo code. The spectra were filtered with various thicknesses of Al, Rh, Mo or Cu. An initial half value layer (HVL) calculation was made using the anode and filter material. A range of the HVL values was produced with the addition of small thicknesses of polymethyl methacrylate (PMMA) as a surrogate for the breast compression paddle, to produce a range of HVL values at each tube voltage. Using a spectral weighting method, D(g)N coefficients for the generated spectra were calculated for breast glandular densities of 0%, 12.5%, 25%, 37.5%, 50% and 100% for a range of compressed breast thicknesses from 3 to 8 cm. Eleven tables of normalized glandular dose (D(g)N) coefficients were produced for the following anode/filter combinations: W + 50 μm Ag, W + 500 μm Al, W + 700 μm Al, W + 200 μm Cu, W + 300 μm Cu, W + 50 μm Rh, Mo + 400 μm Cu, Mo + 30 μm Mo, Mo + 25 μm Rh, Rh + 400 μm Cu and Rh + 25 μm Rh. Where possible, these results were compared to previously published D(g)N values and were found to be on average less than 2% different than previously reported values.Over 200 pages of D(g)N coefficients were computed for modeled x-ray system spectra that are used in a number of new breast imaging applications. The reported values were found to be in excellent agreement when compared to published values.

Radiological Protection in Cone Beam Computed Tomography (CBCT). ICRP Publication 129

The objective of this publication is to provide guidance on radiological protection in the new technology of cone beam computed tomography (CBCT). Publications 87 and 102 dealt with patient dose management in computed tomography (CT) and multi-detector CT. The new applications of CBCT and the associated radiological protection issues are substantially different from those of conventional CT. The perception that CBCT involves lower doses was only true in initial applications. CBCT is now used widely by specialists who have little or no training in radiological protection. This publication provides recommendations on radiation dose management directed at different stakeholders, and covers principles of radiological protection, training, and quality assurance aspects. Advice on appropriate use of CBCT needs to be made widely available. Advice on optimisation of protection when using CBCT equipment needs to be strengthened, particularly with respect to the use of newer features of the equipment. Manufacturers should standardise radiation dose displays on CBCT equipment to assist users in optimisation of protection and comparisons of performance. Additional challenges to radiological protection are introduced when CBCT-capable equipment is used for both fluoroscopy and tomography during the same procedure. Standardised methods need to be established for tracking and reporting of patient radiation doses from these procedures. The recommendations provided in this publication may evolve in the future as CBCT equipment and applications evolve. As with previous ICRP publications, the Commission hopes that imaging professionals, medical physicists, and manufacturers will use the guidelines and recommendations provided in this publication for implementation of the Commission's principle of optimisation of protection of patients and medical workers, with the objective of keeping exposures as low as reasonably achievable, taking into account economic and societal factors, and consistent with achieving the necessary medical outcomes.

Task-based optimization of dedicated breast CT via Hotelling observer metrics

PURPOSE

The purpose of this work is to develop and demonstrate a set of practical metrics for CT systems optimization. These metrics, based on the Hotelling observer (HO) figure of merit, are task-based. The authors therefore take the specific example of optimizing a dedicated breast CT system, including the reconstruction algorithm, for two relevant tasks, signal detection and Rayleigh discrimination.

METHODS

A dedicated breast CT system is simulated using specifications in the literature from an existing prototype. The authors optimize configuration and image reconstruction algorithm parameters for two tasks: the detection of simulated microcalcifications and the discrimination of two adjacent, high-contrast signals, known as the Rayleigh discrimination task. The effects on task performance of breast diameter, signal location, image grid size, projection view number, and reconstruction filter were all investigated. Two HO metrics were evaluated: the percentage of correct decisions in a two-alternative forced choice experiment (equivalent to area under the ROC curve or AUC), and the HO efficiency, defined as the squared ratio of HO signal-to-noise ratio (SNR) in the reconstructed image to HO SNR in the projection data.

RESULTS

The ease and efficiency of the HO metric computation allows a rapid high-resolution survey of many system parameters. Optimization of a range of system parameters using the HO results in images that subjectively appear optimal for the tasks investigated. Further, the results of assessment through the HO reproduce closely many existing results in the literature regarding the impact of parameter selection on image quality.

CONCLUSIONS

This study demonstrates the utility of a task-based approach to system design, evaluation, and optimization. The methodology presented is equally applicable to determining the impact of a wide range of factors, including patient parameters, system and acquisition design, and the reconstruction algorithm. The results demonstrate the versatility of the proposed HO formalism by not only generating a set of parameters that are optimal for a given task but also by qualitatively reproducing many existing results from the breast CT literature. Meanwhile, the implementation of the proposed methodology is straightforward and entirely simulation-based. This is an attractive feature for many system optimization problems, where the goal is to analyze the individual system components such as the image reconstruction algorithm. Final assessment of the system as a whole should be based also on real data studies.

Simulated lesion, human observer performance comparison between thin-section dedicated breast CT images versus computed thick-section simulated projection images of the breast

The objective of this study was to compare the lesion detection performance of human observers between thin-section computed tomography images of the breast, with thick-section (>40 mm) simulated projection images of the breast. Three radiologists and six physicists each executed a two alterative force choice (2AFC) study involving simulated spherical lesions placed mathematically into breast images produced on a prototype dedicated breast CT scanner. The breast image data sets from 88 patients were used to create 352 pairs of image data. Spherical lesions with diameters of 1, 2, 3, 5, and 11 mm were simulated and adaptively positioned into 3D breast CT image data sets; the native thin section (0.33 mm) images were averaged to produce images with different slice thicknesses; average section thicknesses of 0.33, 0.71, 1.5 and 2.9 mm were representative of breast CT; the average 43 mm slice thickness served to simulate simulated projection images of the breast.The percent correct of the human observer's responses were evaluated in the 2AFC experiments. Radiologists lesion detection performance was significantly (p < 0.05) better in the case of thin-section images, compared to thick section images similar to mammography, for all but the 1 mm lesion diameter lesions. For example, the average of three radiologist's performance for 3 mm diameter lesions was 92% correct for thin section breast CT images while it was 67% for the simulated projection images. A gradual reduction in observer performance was observed as the section thickness increased beyond about 1 mm. While a performance difference based on breast density was seen in both breast CT and the projection image results, the average radiologist performance using breast CT images in dense breasts outperformed the performance using simulated projection images in fatty breasts for all lesion diameters except 11 mm. The average radiologist performance outperformed that of the average physicist observer, however trends in performance were similar. Human observers demonstrate significantly better mass-lesion detection performance on thin-section CT images of the breast, compared to thick-section simulated projection images of the breast.

Region of interest based Hotelling observer for computed tomography with comparison to alternative methods

We compare several approaches to estimation of Hotelling observer (HO) performance in x-ray computed tomography (CT). We consider the case where the signal of interest is small so that the reconstructed image can be restricted to a small region of interest (ROI) surrounding the signal. This reduces the dimensionality of the image covariance matrix so that direct computation of HO metrics within the ROI is feasible. We propose that this approach is directly applicable to systems optimization in CT; however, many alternative approaches exist, which make computation of HO performance tractable through a range of approximations, assumptions, or estimation strategies. Here, we compare several of these methods, including the use of Laguerre-Gauss channels, discrete Fourier domain computation of the HO (which assumes noise stationarity), and two approaches to HO estimation through samples of noisy images. Since our method computes HO performance exactly within an ROI, this allows us to investigate the validity of the assumptions inherent in various common approaches to HO estimation, such as the stationarity assumption in the case of the discrete Fourier transform domain method.

A breast-specific, negligible-dose scatter correction technique for dedicated cone-beam breast CT: a physics-based approach to improve Hounsfield Unit accuracy

The purpose of this research was to develop a method to correct the cupping artifact caused from x-ray scattering and to achieve consistent Hounsfield Unit (HU) values of breast tissues for a dedicated breast CT (bCT) system. The use of a beam passing array (BPA) composed of parallel-holes has been previously proposed for scatter correction in various imaging applications. In this study, we first verified the efficacy and accuracy using BPA to measure the scatter signal on a cone-beam bCT system. A systematic scatter correction approach was then developed by modeling the scatter-to-primary ratio (SPR) in projection images acquired with and without BPA. To quantitatively evaluate the improved accuracy of HU values, different breast tissue-equivalent phantoms were scanned and radially averaged HU profiles through reconstructed planes were evaluated. The dependency of the correction method on object size and number of projections was studied. A simplified application of the proposed method on five clinical patient scans was performed to demonstrate efficacy. For the typical 10-18 cm breast diameters seen in the bCT application, the proposed method can effectively correct for the cupping artifact and reduce the variation of HU values of breast equivalent material from 150 to 40 HU. The measured HU values of 100% glandular tissue, 50/50 glandular/adipose tissue, and 100% adipose tissue were approximately 46, -35, and -94, respectively. It was found that only six BPA projections were necessary to accurately implement this method, and the additional dose requirement is less than 1% of the exam dose. The proposed method can effectively correct for the cupping artifact caused from x-ray scattering and retain consistent HU values of breast tissues.

The potential role of dedicated 3D breast CT as a diagnostic tool: review and early clinical examples

Mammography is the gold standard in routine screening for the detection of breast cancer in the general population. However, limitations in sensitivity, particularly in dense breasts, has motivated the development of alternative imaging techniques such as digital breast tomosynthesis, whole breast ultrasound, breast-specific gamma imaging, and more recently dedicated breast computed tomography or "breast CT". Virtually all diagnostic work-ups of asymptomatic nonpalpable findings arise from screening mammography. In most cases, diagnostic mammography and ultrasound are sufficient for diagnosis, with magnetic resonance imaging (MRI) playing an occasional role. Digital breast tomosynthesis, a limited-angle tomographic technique, is increasingly being used for screening. Dedicated breast CT has full three-dimensional (3D) capability with near-isotropic resolution, which could potentially improve diagnostic accuracy. In current dedicated breast CT clinical prototypes, 300-500 low-dose projections are acquired in a circular trajectory around the breast using a flat panel detector, followed by image reconstruction to provide the 3D breast volume. The average glandular dose to the breast from breast CT can range from as little as a two-view screening mammogram to approximately that of a diagnostic mammography examination. Breast CT displays 3D images of the internal structures of the breast; therefore, evaluation of suspicious features like microcalcifications, masses, and asymmetries can be made in multiple anatomical planes from a single scan. The potential role of breast CT for diagnostic imaging is illustrated here through clinical examples such as imaging soft tissue abnormalities and microcalcifications. The potential for breast CT to serve as an imaging tool for extent of disease evaluation and for monitoring neo-adjuvant chemotherapy response is also illustrated.

Measurement of breast tissue composition with dual energy cone-beam computed tomography: a postmortem study

PURPOSE

To investigate the feasibility of a three-material compositional measurement of water, lipid, and protein content of breast tissue with dual kVp cone-beam computed tomography (CT) for diagnostic purposes.

METHODS

Simulations were performed on a flat panel-based computed tomography system with a dual kVp technique in order to guide the selection of experimental acquisition parameters. The expected errors induced by using the proposed calibration materials were also estimated by simulation. Twenty pairs of postmortem breast samples were imaged with a flat-panel based dual kVp cone-beam CT system, followed by image-based material decomposition using calibration data obtained from a three-material phantom consisting of water, vegetable oil, and polyoxymethylene plastic. The tissue samples were then chemically decomposed into their respective water, lipid, and protein contents after imaging to allow direct comparison with data from dual energy decomposition.

RESULTS

Guided by results from simulation, the beam energies for the dual kVp cone-beam CT system were selected to be 50 and 120 kVp with the mean glandular dose divided equally between each exposure. The simulation also suggested that the use of polyoxymethylene as the calibration material for the measurement of pure protein may introduce an error of -11.0%. However, the tissue decomposition experiments, which employed a calibration phantom made out of water, oil, and polyoxymethylene, exhibited strong correlation with data from the chemical analysis. The average root-mean-square percentage error for water, lipid, and protein contents was 3.58% as compared with chemical analysis.

CONCLUSIONS

The results of this study suggest that the water, lipid, and protein contents can be accurately measured using dual kVp cone-beam CT. The tissue compositional information may improve the sensitivity and specificity for breast cancer diagnosis.

Constrained TpV Minimization for Enhanced Exploitation of Gradient Sparsity: Application to CT Image Reconstruction

Exploiting sparsity in the image gradient magnitude has proved to be an effective means for reducing the sampling rate in the projection view angle in computed tomography (CT). Most of the image reconstruction algorithms, developed for this purpose, solve a nonsmooth convex optimization problem involving the image total variation (TV). The TV seminorm is the ℓ₁ norm of the image gradient magnitude, and reducing the ℓ₁ norm is known to encourage sparsity in its argument. Recently, there has been interest in employing nonconvex ℓ_p quasinorms with 0<p<1 for sparsity exploiting image reconstruction, which is potentially more effective than ℓ₁ because nonconvex ℓ_p is closer to ℓ₀-a direct measure of sparsity. This paper develops algorithms for constrained minimization of the total p-variation (TpV), ℓ_p of the image gradient. Use of the algorithms is illustrated in the context of breast CT-an imaging modality that is still in the research phase and for which constraints on X-ray dose are extremely tight. The TpV-based image reconstruction algorithms are demonstrated on computer simulated data for exploiting gradient magnitude sparsity to reduce the projection view angle sampling. The proposed algorithms are applied to projection data from a realistic breast CT simulation, where the total X-ray dose is equivalent to two-view digital mammography. Following the simulation survey, the algorithms are then demonstrated on a clinical breast CT data set.

Breast density quantification with cone-beam CT: a post-mortem study

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The per cent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson's r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation.

Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system

PURPOSE

To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions.

METHODS

Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples.

RESULTS

The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%.

CONCLUSIONS

The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement.

Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study

A simple and accurate measurement of breast density is crucial for the understanding of its impact in breast cancer risk models. The feasibility to quantify volumetric breast density with a photon-counting spectral mammography system has been investigated using both computer simulations and physical phantom studies. A computer simulation model involved polyenergetic spectra from a tungsten anode x-ray tube and a Si-based photon-counting detector has been evaluated for breast density quantification. The figure-of-merit (FOM), which was defined as the signal-to-noise ratio of the dual energy image with respect to the square root of mean glandular dose, was chosen to optimize the imaging protocols, in terms of tube voltage and splitting energy. A scanning multi-slit photon-counting spectral mammography system has been employed in the experimental study to quantitatively measure breast density using dual energy decomposition with glandular and adipose equivalent phantoms of uniform thickness. Four different phantom studies were designed to evaluate the accuracy of the technique, each of which addressed one specific variable in the phantom configurations, including thickness, density, area and shape. In addition to the standard calibration fitting function used for dual energy decomposition, a modified fitting function has been proposed, which brought the tube voltages used in the imaging tasks as the third variable in dual energy decomposition. For an average sized 4.5 cm thick breast, the FOM was maximized with a tube voltage of 46 kVp and a splitting energy of 24 keV. To be consistent with the tube voltage used in current clinical screening exam (∼32 kVp), the optimal splitting energy was proposed to be 22 keV, which offered a FOM greater than 90% of the optimal value. In the experimental investigation, the root-mean-square (RMS) error in breast density quantification for all four phantom studies was estimated to be approximately 1.54% using standard calibration function. The results from the modified fitting function, which integrated the tube voltage as a variable in the calibration, indicated a RMS error of approximately 1.35% for all four studies. The results of the current study suggest that photon-counting spectral mammography systems may potentially be implemented for an accurate quantification of volumetric breast density, with an RMS error of less than 2%, using the proposed dual energy imaging technique.