Lynda C. Ikejimba

Development and Application of a Suite of 4-D Virtual Breast Phantoms for Optimization and Evaluation of Breast Imaging Systems

Mammography is currently the most widely utilized tool for detection and diagnosis of breast cancer. However, in women with dense breast tissue, tissue overlap may obscure lesions. Digital breast tomosynthesis can reduce tissue overlap. Furthermore, imaging with contrast enhancement can provide additional functional information about lesions, such as morphology and kinetics, which in turn may improve lesion identification and characterization. The performance of these imaging techniques is strongly dependent on the structural composition of the breast, which varies significantly among patients. Therefore, imaging system and imaging technique optimization should take patient variability into consideration. Furthermore, optimization of imaging techniques that employ contrast agents should include the temporally varying breast composition with respect to the contrast agent uptake kinetics. To these ends, we have developed a suite of 4-D virtual breast phantoms, which are incorporated with the kinetics of contrast agent propagation in different tissues and can realistically model normal breast parenchyma as well as benign and malignant lesions. This development presents a new approach in performing simulation studies using truly anthropomorphic models. To demonstrate the utility of the proposed 4-D phantoms, we present a simplified example study to compare the performance of 14 imaging paradigms qualitatively and quantitatively.

A novel physical anthropomorphic breast phantom for 2D and 3D x‐ray imaging

Purpose: Physical phantoms are central to the evaluation of 2D and 3D breast‐imaging systems. Currently, available physical phantoms have limitations including unrealistic uniform background structure, large expense, or excessive fabrication time. The purpose of this work is to outline a method for rapidly creating realistic, inexpensive physical anthropomorphic phantoms for use in full‐field digital mammography (FFDM) and digital breast tomosynthesis (DBT). Methods: The phantom was first modeled using analytical expressions and then discretized into voxels of a specified size. The interior of the breast was divided into glandular and adipose tissue classes using Voronoi segmentation, and additional structures like blood vessels, chest muscle, and ligaments were added. The physical phantom was then fabricated from the virtual model in a slice by slice fashion through inkjet printing, using parchment paper and a radiopaque ink containing 33% (I33%) or 25% (I25%) iohexol by volume. Three types of parchment paper (P1, P2, and P3) were examined. The phantom materials were characterized in terms of their effective linear attenuation coefficients (μeff) using full‐field digital mammography (FFDM) and their energy‐dependent linear attenuation coefficients (μ(E)) using a spectroscopic energy discriminating detector system. The printing method was further validated on the basis of accuracy, print consistency, and the reproducibility of ink batches. Results: The μeff of two types of parchment paper were close to that of adipose tissue, with μeff = 0.61 ± 0.05 cm−1 for P1, 0.61 ± 0.04 cm−1 for P2, and 0.57 ± 0.03 cm−1 for adipose tissue. The addition of the iodinated ink increased the effective attenuation to that of glandular tissue, with μeff = 0.89 ± 0.06 cm−1 for P1 + I25% and 0.94 ± 0.06 cm−1 for P1 + I33% compared to 0.90 ± 0.03 cm−1 for glandular tissue. Spectroscopic measurements showed a good match between the parchment paper and reference values for adipose and glandular tissues across photon energies. Good accuracy was found between the model and the printed phantom by comparing a FFDM of the virtual model simulated through Monte Carlo with a real FFDM of the fully printed phantom. High consistency was found over multiple prints, with 3% variability in mean ink signal across various samples. Reproducibility of ink consistency was very high with <1% variation signal from multiple batches of ink. Imaging of the phantom using FFDM and DBT systems showed promising utility for 2D and 3D imaging. Conclusions: A novel, realistic breast phantom can be created using an analytically defined breast model and readily available materials. The work provides a method to fabricate any virtual phantom in a manner that is accurate, inexpensive, easily accessible, and can be made with different materials or breast models.

A quantitative metrology for performance characterization of five breast tomosynthesis systems based on an anthropomorphic phantom

PURPOSE In medical imaging systems, proper rendition of anatomy is essential in discerning normal tissue from disease. Currently, digital breast tomosynthesis (DBT) systems are evaluated using subjective evaluation of lesion visibility in uniform phantoms. This study involved the development of a new methodology to objectively measure the rendition of a 3D breast model by an anthropomorphic breast phantom, and its implementation on five clinical DBT systems of different makes and models. METHODS A 3D, patient-based breast phantom was fabricated based on XCAT breast models. This phantom was imaged on representative breast tomosynthesis systems. The ability of tomosynthesis systems to accurately reproduce the 3D structure of the breast was assessed by computational analysis of the resultant images in terms of three groups of indices: contrast index (CI), reflective of local difference between adipose and glandular material; adipose variability index (AVI), reflective of contributions of noise and artifacts within uniform adipose regions; and contrast detectability, which describes contrast against local background variability and is described by contrast variability index (CVI), coefficient of variation (COV), contrast to adipose variability index (CAVI), and contrast to noise ratio index (CNRI). The indices were obtained by comparing the image data to the gold standard 3D distribution of breast tissue in the model. Corresponding indices were measured within variable region of interest (ROI) sizes ranging from 10 to 37 mm. The characterization was performed on five tomosynthesis systems: Fuji Aspire Crystal, GE Essential, Hologic Dimension, IMS Giotto, and Siemens Inspiration, all evaluated at a fixed dose of 1.5 mGy average glandular dose, anonymized in random order from A to E. RESULTS Results are provided as a function of ROI size. The systems ranked orders in terms of CI with values of 7.4%, 7.0%, 6.9%, 6.4%, and 5.2% for systems A-E, respectively. This system ranking was identical for CNRI. Both CI and CNRI were constant over ROI size. The ranking was similar for CVI. The COV also changed little with ROI size and was similar across systems. For 10 mm ROIs, the average system COV was 0.7, which reduced to 0.5 with 37 mm ROIs. Two systems (A and B) exhibited highest AVI values when measured in 10 mm ROIs. This, however, was ROI-size-dependent with the three other systems (C-E) yielding higher AVI values when measured with 37 mm ROIs. Two systems (B and E) showed inferior CAVI compared to others. CONCLUSIONS The quality of rendition tracked with differences in image appearance across systems. The findings illustrate that the anthropomorphic phantom can be used as a basis to extract quantitative values of image attributes in DBT.

Assessing task performance in FFDM, DBT, and synthetic mammography using uniform and anthropomorphic physical phantoms.

PURPOSE The purpose of this study is to quantify the differences in detectability between full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) for challenging, low contrast signals, in the context of both a uniform and an anthropomorphic, textured phantom. METHODS Images of the phantoms were acquired using a Hologic Selenia Dimensions system. Images were taken at 50%, 100%, and 200% of the dose delivered under automatic exposure control (AEC). Low-contrast disks, created using an inkjet printer with iodine-doped ink, were inserted into the phantom. The disks varied in diameter from 210 to 630 μm, and in local contrast from 1.1% to 2.8% in regular increments. Human observers located the disks in a 4 alternative forced choice experiment. Proportion correct (PC) was computed as the number of correct localizations out of the total number of tries. RESULTS Overall, scores from FFDM and DBT were consistently greater than scores from SM. At an exposure corresponding to the AEC setting, mean PC scores for the largest disks with the uniform phantom were 0.80 for FFDM, 0.83 for DBT, and 0.66 for SM, with the same rank ordering at other doses. Scores were similar but lower for the nonuniform background. At an exposure twice the AEC setting, however, the difference between uniform and nonuniform scores was most pronounced for DBT alone. Differences between scores for FFDM and SM were statistically significant, while those between FFDM and DBT were not. Scores were used to compute the minimum contrast level needed to reach 62.5% detection rate. The minimum contrast for SM was 36%-81% higher compared to FFDM or DBT, in either background. CONCLUSIONS This study shows that an anthropomorphic phantom and lesions inserts may be used to conduct a reader study. Detectability was significantly lower for synthetic mammography than for FFDM or DBT, for all conditions. Additionally, observer performance was consistently lower for the anthropomorphic phantom, indicating the greater challenge due to anatomical background. Because of this, it may be important to use realistic phantoms in observer studies in order to draw conclusions that are more clinically relevant.

Development of a dynamic 4D anthropomorphic breast phantom for contrast-based breast imaging

Mammography is currently the most widely accepted tool for detection and diagnosis of breast cancer. However, the sensitivity of mammography is reduced in women with dense breast tissue due to tissue overlap, which may obscure lesions. Digital breast tomosynthesis with contrast enhancement reduces tissue overlap and provides additional functional information about lesions (i.e. morphology and kinetics), which in turn may improve lesion characterization. The performance of such techniques is highly dependent on the structural composition of the breast, which varies significantly across patients. Therefore, optimization of breast imaging systems should be done with respect to this patient versatility. Furthermore, imaging techniques that employ contrast require the inclusion of a temporally varying breast composition with respect to the contrast agent kinetics to enable the optimization of the system. To these ends, we have developed a dynamic 4D anthropomorphic breast phantom, which can be used for optimizing a breast imaging system by incorporating material characteristics. The presented dynamic phantom is based on two recently developed anthropomorphic breast phantoms, which can be representative of a whole population through their randomized anatomical feature generation and various compression levels. The 4D dynamic phantom is incorporated with the kinetics of contrast agent uptake in different tissues and can realistically model benign and malignant lesions. To demonstrate the utility of the proposed dynamic phantom, contrast-enhanced digital mammography and breast tomosynthesis were simulated where a ray-tracing algorithm emulated the projections, a filtered back projection algorithm was used for reconstruction, and dual-energy and temporal subtractions were performed and compared.

A physical breast phantom for 2D and 3D x-ray imaging made through inkjet printing

Physical breast phantoms are used for imaging evaluation studies with 2D and 3D breast x-ray systems, serving as surrogates for human patients. However, there is a presently a limited selection of available phantoms that are realistic, in terms of containing the complex tissue architecture of the human breast. In addition, not all phantoms can be successfully utilized for both 2D and 3D breast imaging. Additionally, many of the phantoms are uniform or unrealistic in appearance, expensive, or difficult to obtain. The purpose of this work was to develop a new method to generate realistic physical breast phantoms using easy to obtain and inexpensive materials. First, analytical modeling was used to design a virtual model, which was then compressed using finite element modeling. Next, the physical phantom was realized through inkjet printing with a standard inkjet printer using parchment paper and specialized inks, formulated using silver nanoparticles and a bismuth salt. The printed phantom sheets were then aligned and held together using a custom designed support plate made of PMMA, and imaged on clinical FFDM and DBT systems. Objects of interest were also placed within the phantom to simulate microcalcifications, pathologies that often occur in the breast. The linear attenuation coefficients of the inks and parchment were compared against tissue equivalent samples and found to be similar to breast tissue. The phantom is promising for use in imaging studies and developing QC protocols.

Comparison of model and human observer performance in FFDM, DBT, and synthetic mammography

Reader studies are important in assessing breast imaging systems. The purpose of this work was to assess task-based performance of full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) using different phantom types, and to determine an accurate observer model for human readers. Images were acquired on a Hologic Selenia Dimensions system with a uniform and anthropomorphic phantom. A contrast detail insert of small, low-contrast disks was created using an inkjet printer with iodine-doped ink and inserted in the phantoms. The disks varied in diameter from 210 to 630 μm, and in contrast from 1.1% contrast to 2.2% in regular increments. Human and model observers performed a 4-alternative forced choice experiment. The models were a non-prewhitening matched filter with eye model (NPWE) and a channelized Hotelling observer with either Gabor channels (Gabor-CHO) or Laguerre-Gauss channels (LG-CHO). With the given phantoms, reader scores were higher in FFDM and DBT than SM. The structure in the phantom background had a bigger impact on outcome for DBT than for FFDM or SM. All three model observers showed good correlation with humans in the uniform background, with ρ between 0.89 and 0.93. However, in the structured background, only the CHOs had high correlation, with ρ=0.92 for Gabor-CHO, 0.90 for LG-CHO, and 0.77 for NPWE. Because results of any analysis can depend on the phantom structure, conclusions of modality performance may need to be taken in the context of an appropriate model observer and a realistic phantom.

A task-based comparison of two reconstruction algorithms for digital breast tomosynthesis

Digital breast tomosynthesis (DBT) generates 3-D reconstructions of the breast by taking X-Ray projections at various angles around the breast. DBT improves cancer detection as it minimizes tissue overlap that is present in traditional 2-D mammography. In this work, two methods of reconstruction, filtered backprojection (FBP) and the Newton-Raphson iterative reconstruction were used to create 3-D reconstructions from phantom images acquired on a breast tomosynthesis system. The task based image analysis method was used to compare the performance of each reconstruction technique. The task simulated a 10mm lesion within the breast containing iodine concentrations between 0.0mg/ml and 8.6mg/ml. The TTF was calculated using the reconstruction of an edge phantom, and the NPS was measured with a structured breast phantom (CIRS 020) over different exposure levels. The detectability index d’ was calculated to assess image quality of the reconstructed phantom images. Image quality was assessed for both conventional, single energy and dual energy subtracted reconstructions. Dose allocation between the high and low energy scans was also examined. Over the full range of dose allocations, the iterative reconstruction yielded a higher detectability index than the FBP for single energy reconstructions. For dual energy subtraction, detectability index was maximized when most of the dose was allocated to the high energy image. With that dose allocation, the performance trend for reconstruction algorithms reversed; FBP performed better than the corresponding iterative reconstruction. However, FBP performance varied very erratically with changing dose allocation. Therefore, iterative reconstruction is preferred for both imaging modalities despite underperforming dual energy FBP, as it provides stable results.

Estimating breast density with dual energy mammography: a simple model based on calibration phantoms

Dual energy digital mammography has been used to suppress specific breast tissue, primarily for the purpose of iodine contrast-enhanced imaging. Another application of dual energy digital mammography is to estimate breast density, as defined by the fraction of glandular tissue, by suppressing adipose tissue. Adipose equivalent phantoms were used to derive the weighting factor for dual energy subtraction at 2, 4, 6, and 8 cm thickness. For each thickness besides 8 cm, measurements were taken over a range of densities (0, 50, and 100%) and used for calibration measurements to model a density map. Once the density map was verified with uniform slabs, the density map was evaluated with 50/50 CIRS 020 phantom at 2, 4, and 6 cm thickness and demonstrated the feasibility of using dual energy subtraction to estimate breast density on complex phantoms.

Report of AAPM Task Group 162: Software for planar image quality metrology

PURPOSE The AAPM Task Group 162 aimed to provide a standardized approach for the assessment of image quality in planar imaging systems. This report offers a description of the approach as well as the details of the resultant software bundle to measure detective quantum efficiency (DQE) as well as its basis components and derivatives. METHODS The methodology and the associated software include the characterization of the noise power spectrum (NPS) from planar images acquired under specific acquisition conditions, modulation transfer function (MTF) using an edge test object, the DQE, and effective DQE (eDQE). First, a methodological framework is provided to highlight the theoretical basis of the work. Then, a step-by-step guide is included to assist in proper execution of each component of the code. Lastly, an evaluation of the method is included to validate its accuracy against model-based and experimental data. RESULTS The code was built using a Macintosh OSX operating system. The software package contains all the source codes to permit an experienced user to build the suite on a Linux or other *nix type system. The package further includes manuals and sample images and scripts to demonstrate use of the software for new users. The results of the code are in close alignment with theoretical expectations and published results of experimental data. CONCLUSIONS The methodology and the software package offered in AAPM TG162 can be used as baseline for characterization of inherent image quality attributes of planar imaging systems.