Breast dosimetry using high-resolution voxel phantoms

Trends in patient dose and compression force for digital (DR) mammography systems over an eleven-year period

This study evaluated trends in patient dose and compression force for screening digital (DR) mammography systems. The results of five audits (carried out in 2011, 2014, 2018, 2020 and 2022) were compared. For every audit, anonymised screening examinations from each system consisting of the standard craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts were analysed. Exposure parameters were extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the mean glandular dose (MGD) for each image was calculated. Trends in the distribution of MGD, compressed breast thickness, compression force and compression force per radiographer were investigated. The mean MGD per image (and mean compressed breast thickness) was 1.20 mGy (58 mm), 1.53 mGy (59 mm), 1.83 mGy (61 mm), 1.94 mGy (60 mm) and 2.11 mGy (61 mm) for 2011, 2014, 2018, 2020 and 2022 respectively. The mean (and standard deviation) compression force was 114 (32) N, 112 (29) N, 108 (27) N, 104 (24) N and 100 (23) N for 2011, 2014, 2018, 2020 and 2022 respectively. The mean MGD per image has increased over time but remains below internationally established Diagnostic Reference Levels (DRLs). This increase is primarily due to a change in the distribution of the different manufacturers and digital detector technologies, rather than an increase in the dose of the individual systems over time. The mean compression force has decreased over time in response to client feedback surveys. The standard deviation has also reduced, indicating more consistent application of force.

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.

Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the 'dense region'); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the 'diffuse region'). U-Net was trained to segment the fibroglandular tissue region with an adaptive moment estimation optimiser, five-fold cross-validated with 400 training and 100 validation mammograms, and tested with 203 mammograms. The breast density and MGD were calculated using the van Engeland and Dance formulas, respectively, and compared between U-Net and the ground truth with the Dice similarity coefficient and Bland-Altman analysis. Dice similarity coefficients between U-Net and the ground truth were 0.895 and 0.939 for the dense and diffuse regions, respectively. In the Bland-Altman analysis, no proportional or fixed errors were discovered in either the dense or diffuse region for breast density, whereas a slight proportional error was discovered in both regions for the MGD (the slopes of the regression lines were -0.0299 and -0.0443 for the dense and diffuse regions, respectively). Consequently, the U-Net and ground truth were deemed equivalent (interchangeable) for breast density and compatible (interchangeable following four simple arithmetic operations) for MGD. U-Net-based segmentation of the fibroglandular tissue region was satisfactory for both regions, providing reliable segmentation for breast density and MGD calculations. U-Net will be useful in developing a reliable individualised screening-mammography programme, instead of relying on the visual judgement of mammography experts.

PERFORMANCE COMPARISON OF SYSTEMS WITH FULL-FIELD DIGITAL MAMMOGRAPHY, DIGITAL BREAST TOMOSYNTHESIS AND CONTRAST-ENHANCED SPECTRAL MAMMOGRAPHY

The purpose is to compare full-field digital mammography (FFDM), digital breast tomosynthesis (DBT) and contrast-enhanced spectral mammography (CESM) technologies on three mammography systems in terms of image quality and patient dose. Two Senographe Essential with DBT and CESM (denoted S1 and S2) and one Selenia Dimensions (S3) with FFDM and DBT were considered. Dosimetry methods recommended in the European protocol were used. Image quality was tested with CDMAM in FFDM and DBT and with ideal observer method in FFDM. Mean values of mean glandular dose (MGD) from whole patient samples on S1, S2 and S3 were as follows: FFDM 1.65, 1.84 and 2.23 mGy; DBT 2.03, 1.96 and 2.87 mGy; CESM 2.65 and 3.16 mGy, respectively. S3 exhibited better low-contrast detectability for the smallest sized discs of CDMAM and ideal observer in FFDM, and for the largest sized discs in DBT, at similar dose levels.

VIRTUAL CLINICAL TRIALS IN MEDICAL IMAGING SYSTEM EVALUATION AND OPTIMISATION

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation

The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly used in breast cancer screening and diagnostics. Still, the severely limited 3rd dimension information in DBT has not been used, until now, to estimate the true breast density or the patient-specific dose. This study proposes a reconstruction algorithm for DBT based on deep learning specifically optimized for these tasks. The algorithm, which we name DBToR, is based on unrolling a proximal-dual optimization method. The proximal operators are replaced with convolutional neural networks and prior knowledge is included in the model. This extends previous work on a deep learning-based reconstruction model by providing both the primal and the dual blocks with breast thickness information, which is available in DBT. Training and testing of the model were performed using virtual patient phantoms from two different sources. Reconstruction performance, and accuracy in estimation of breast density and radiation dose, were estimated, showing high accuracy (density <±3%; dose <±20%) without bias, significantly improving on the current state-of-the-art. This work also lays the groundwork for developing a deep learning-based reconstruction algorithm for the task of image interpretation by radiologists.

Fibroglandular tissue distribution in the breast during mammography and tomosynthesis based on breast CT data: A patient-based characterization of the breast parenchyma

PURPOSE

To develop a patient-based breast density model by characterizing the fibroglandular tissue distribution in patient breasts during compression for mammography and digital breast tomosynthesis (DBT) imaging.

METHODS

In this prospective study, 88 breast images were acquired using a dedicated breast computed tomography (CT) system. The breasts in the images were classified into their three main tissue components and mechanically compressed to mimic the positioning for mammographic acquisition of the craniocaudal (CC) and mediolateral oblique (MLO) views. The resulting fibroglandular tissue distribution during these compressions was characterized by dividing the compressed breast volume into small regions, for which the median and the 25th and 75th percentile values of local fibroglandular density were obtained in the axial, coronal, and sagittal directions. The best fitting function, based on the likelihood method, for the median distribution was obtained in each direction.

RESULTS

The fibroglandular tissue tends to concentrate toward the caudal (about 15% below the midline of the breast) and anterior regions of the breast, in both the CC- and MLO-view compressions. A symmetrical distribution was found in the MLO direction in the case of the CC-view compression, while a shift of about 12% toward the lateral direction was found in the MLO-view case.

CONCLUSIONS

The location of the fibroglandular tissue in the breast under compression during mammography and DBT image acquisition is a major factor for determining the actual glandular dose imparted during these examinations. A more realistic model of the parenchyma in the compressed breast, based on patient image data, was developed. This improved model more accurately reflects the fibroglandular tissue spatial distribution that can be found in patient breasts, and therefore might aid in future studies involving radiation dose and/or cancer development risk estimation.

Three-layer heterogeneous mammographic phantoms for Monte Carlo simulation of normalized glandular dose coefficients in mammography

Normalized glandular dose (DgN) coefficients obtained using homogeneous breast phantoms are commonly used in breast dosimetry for mammography. However, glandular tissue is heterogeneously distributed in the breast. This study aimed to construct three-layer heterogeneous mammographic phantoms (THEPs) to examine the effect of glandular distribution on DgN coefficient. Each layer of THEPs was set to 25%, 50%, or 75% glandular fraction to emulate heterogeneous glandular distribution. Monte Carlo simulation was performed to attain mean glandular dose (MGD) and air kerma at 22-36 kVp and W/Al, W/Rh, and W/Ag target-filter combinations. The heterogeneous DgN coefficient was calculated as functions of the mean glandular fraction (MGF), breast thickness, tube voltage, and half-value layer. At 50% MGF, the heterogeneous DgN coefficients for W/Al, W/Rh, and W/Ag differed by 40.3%, 36.7%, and 31.2%. At 9-cm breast thickness, the DgN values of superior and inferior glandular distributions were 25.4% higher and 29.2% lower than those of uniform distribution. The proposed THEPs can be integrated with conventional breast dosimetry to consider the heterogeneous glandular distribution in clinical practice.

Calculating Individual Lifetime Effective Risk from Initial Mean Glandular Dose Arising from the First Screening Mammogram

OBJECTIVES

The objective of the study was to use the initial mean glandular dose (MGD) arising from the first screening mammogram to estimate the individual total screening lifetime effective risk.

METHODS

Organ doses from full-field digital mammography (FFDM) screening exposures (craniocaudal and mediolateral oblique for each breast) were measured using a simulated approach, with average breast thickness and adult ATOM phantoms, on 16 FFDM machines. Doses were measured using thermoluminescent dosimeters accommodated inside the ATOM phantom; examined breast MGD was calculated. Total effective risk during a client's lifetime was calculated for 150 screening scenarios of different screening commencement ages and frequencies. For each scenario, a set of conversion factors were obtained to convert MGD values into total effective risk.

RESULTS

For the 16 FFDM machines, MGD contributes approximately 98% of total effective risk. This contribution is approximately constant for different screening regimes of different screening commencement ages. MGD contribution remains constant, but the risk reduced because the radiosensitivity of all body tissues, including breast tissue, reduces with age. Three sets of conversion factors were obtained for three screening frequencies (annual, biennial, triennial). Three relationship graphs between screening commencement age and total effective risk, as percentages of MGD, were created.

CONCLUSIONS

Graphical representation of total risk could be an easy way to illustrate the total effective risk during a client's lifetime. Screening frequency, commencement age, and MGD are good predictors for total effective risk, generating more understandable data for clients than MGD.

Development of 3D patient-based super-resolution digital breast phantoms using machine learning

Digital phantoms are important tools for optimization and evaluation of x-ray imaging systems, and should ideally reflect the 3D structure of human anatomy and its potential variability. In addition, they need to include a good level of detail at a high enough spatial resolution to accurately model the continuous nature of the human anatomy. A pipeline to increase the spatial resolution of patient-based digital breast phantoms that can be used for computer simulations of breast imaging is proposed. Given a tomographic breast image of finite resolution, the proposed methods can generate a phantom and increase its resolution at will, not only simply through super-sampling, but also by generating additional random glandular details to account for glandular edges and strands to compensate for those that may have not been detected in the original image due to the limited spatial resolution of the imaging system used. The proposed algorithms use supervised learning to predict the loss in glandularity due to limited resolution, and then to realistically recover this loss by learning the mapping between low and high resolution images. They were trained on high-resolution synchrotron images (detector pixel size 60 μm) reconstructed at seven voxel dimensions (60 μm-480 μm), and applied to patient images acquired with a clinical breast CT system (detector pixel size 194 μm) to generate super-resolution phantoms (voxel sizes 68 μm). Several evaluations were made to assess the appropriateness of the developed methods, both with the synchrotron (relative prediction error 0.010  ±  0.004, recovering accuracy 0.95  ±  0.04), and with the clinical images (average glandularity error at 194 μm: 0.15%  ±  0.12%). Finally, a breast radiologist assessed the realism of the developed phantoms by blindly comparing original and phantom images, resulting in not being able to distinguish the real from the phantom images. In conclusion, the proposed method can generate super-resolution phantoms from tomographic breast patient images that can be used for future computer simulations for optimization of new breast imaging technologies.

Prediction of glandularity and breast radiation dose from mammography results in Japanese women

Glandularity has a marked impact on the incidence of breast cancer and the missed lesion rate of mammography. The aim of this study was to develop a novel model for predicting glandularity and patient radiation dose using physical factors that are easily determined prior to mammography. Data regarding glandularity and mean glandular dose were obtained from 331 mammograms. A stepwise multiple regression analysis model was developed to predict glandularity using age, compressed breast thickness and body mass index (BMI), while a model to predict mean glandular dose was created using quantified glandularity, age, compressed breast thickness, height and body weight. The most significant factor for predicting glandularity was age, the influence of which was 1.8 times that of BMI. The most significant factor for predicting mean glandular dose was compressed breast thickness, the influence of which was 1.4 times that of glandularity, 3.5 times that of age and 6.1 times that of height. Both models were statistically significant (both p < 0.0001). Easily determined physical factors were able to explain 42.8% of the total variance in glandularity and 62.4% of the variance in mean glandular dose. Graphical abstract Validation results of the above prediction model made using physical factors in Japanese women. The plotted points of actual vs. prediction glandularity shown in a are distributed in the vicinity of the diagonal line, and the residual plot for predicted glandularity shows an almost random distribution as shown in b. These distributions indicate the appropriateness of the prediction model.

Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

PURPOSE

To validate Monte Carlo (MC)-based breast dosimetry estimations using both a homogeneous and a 3D anthropomorphic breast phantom under polyenergetic irradiation for internal breast dosimetry purposes.

METHODS

Experimental measurements were performed with a clinical digital mammography system (Mammomat Inspiration, Siemens Healthcare), using the x-ray spectrum selected by the automatic exposure control and a tube current-exposure time product of 360 mAs. A homogeneous 50% glandular breast phantom and a 3D anthropomorphic breast phantom were used to investigate the dose at different depths (range 0-4 cm with 1 cm steps) for the homogeneous case and at a depth of 2.25 cm for the anthropomorphic case. Local dose deposition was measured using thermoluminescent dosimeters (TLD), metal oxide semiconductor field-effect transistor dosimeters (MOSFET), and GafChromic™ films. A Geant4-based MC simulation was modified to match the clinical experimental setup. Thirty sensitive volumes (3.2 × 3.2 × 0.38 mm3 ) on the axial-phantom plane were included at each depth in the simulation to characterize the internal dose variation and compare it to the experimental TLD and MOSFET measurements. The experimental 2D dose maps obtained with the GafChromic™ films were compared to the simulated 2D dose distributions.

RESULTS

Due to the energy dependence of the dosimeters and due to x-ray beam hardening, dosimeters based on these three technologies have to be calibrated at each depth of the phantom. As expected, the dose was found to decrease with increasing phantom depth, with the reduction being ~93% after 4 cm for the homogeneous breast phantom. The 2D dose map showed nonuniformities in the dose distribution in the axial plane of the phantom. The mean combined standard uncertainty increased with phantom depth by up to 5.3% for TLD, 6.3% for MOSFET, and 9.6% for GafChromic™ film. In the case of a heterogeneous phantom, the dosimeters are able to detect local dose gradient variations. In particular, GafChromic™ film showed local dose variations of about 46% at the boundaries of two materials.

CONCLUSIONS

Results showed a good agreement between experimental measurements (with TLD and MOSFET) and MC data for both homogeneous and anthropomorphic breast phantoms. Larger discrepancies are found when comparing the GafChromic™ dose values to the MC results due to the inherent less precise nature of the former. MC validations in a heterogeneous background at the level of local dose deposition and in absolute terms play a fundamental role in the development of an accurate method to estimate radiation dose. The potential introduction of a breast dosimetry model involving a nonhomogeneous glandular/adipose tissue composition makes the validation of internal dose distributions estimates crucial.

Integrating mammographic breast density in glandular dose calculation

OBJECTIVE

This work proposes the use of mammographic breast density (MBD) to estimate actual glandular dose (AGD), and assesses how AGD compares to mean glandular dose (MGD) estimated using Dance et al method.

METHODS

A retrospective sample of anonymised mammograms (52,405) was retrieved from a central database. Technical parameters and patient characteristics were exported from the Digital Imaging and Communication in Medicine (DICOM) header using third party software. LIBRA (Laboratory for Individualized Breast Radiodensity Assessment) software package (University of Pennsylvania, Philadelphia, USA) was used to estimate MBDs for each mammogram included in the data set. MGD was estimated using Dance et al method, while AGD was calculated by replacing Dance et al standard glandularities with LIBRA estimated MBDs. A linear regression analysis was used to assess the association between MGD and AGD, and a Bland-Altman analysis was performed to assess their mean difference.

RESULTS

The final data set included 31,097 mammograms from 7728 females. MGD, AGD, and MBD medians were 1.53 , 1.62 mGy and 8% respectively. When stratified per breast thickness ranges, median MBDs were lower than Dance's standard glandularities. There was a strong positive correlation (R2 = 0.987, p < 0.0001) between MGD and AGD although the Bland-Altman analysis revealed a small statistically significant bias of 0.087 mGy between MGD and AGD (p < 0.001).

CONCLUSION

AGD estimated from MBD is highly correlated to MGD from Dance method, albeit the Dance method underestimates dose at smaller CBTs. Advances in knowledge: Our work should provide a stepping-stone towards an individualised dose estimation using automated clinical measures of MBD.

Average absorbed breast dose in mammography: a new possible dose index matching the requirements of the European Directive 2013/59/EURATOM

BACKGROUND

The new European Directive 2013/59/EURATOM requires that patients are informed about the risk associated with ionising radiation and that detailed information on patient exposure is included in the radiological report. This implies a revision of the routinely used dose indexes to obtain quantities related to individual exposure evaluable from acquisition parameters. Here we propose a new mammography dose index consistent with the average glandular dose (AGD).

METHODS

An equation has been developed for calculating the average absorbed breast dose (2ABD). It depends on incident air kerma ka,i and on energy absorption coefficient μen; ka,i can be calculated for each anode-filter combination, based on kVp, mAs, the yield of the tube used Ytb , and the breast thickness d; μen depends on kVp and has been evaluated for each anode-filter combination. 2ABD has been compared to AGD evaluated by Dance or Wu methods, which represent the reference standards, for 20 patients of our university hospital.

RESULTS

The incident air kerma ka,i , calculated as a function of kVp, mAs, Ytb and d, was in good agreement with the same quantity directly measured: the relative uncertainty is < 0.10. The results of the comparison between 2ABD and AGD evaluated by both Dance and Wu methods appear to be consistent within the uncertainties.

CONCLUSIONS

2ABD is easily evaluable for each mammogram from the acquisition parameters. It can be proposed as a new suitable dose index, consistent with AGD, matching the requirements of the 2013 European Directive.

Two-dimensional breast dosimetry improved using three-dimensional breast image data

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.

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.

Breast dose in mammography is about 30% lower when realistic heterogeneous glandular distributions are considered

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.

Benefit to Radiation Risk of Breast-specific Gamma Imaging Compared with Mammography in Screening Asymptomatic Women with Dense Breasts

Purpose To estimate the benefit-to-radiation risk ratios of mammography alone, breast-specific gamma imaging (BSGI) alone, and mammography plus BSGI in women with dense breasts who were asymptomatic and examined in the 2015 study by Rhodes et al. Materials and Methods This study uses previously published breast cancer detection rates and estimates of radiation dose and radiation risk and is, therefore, exempt from institutional review board approval. By using breast cancer detection rates for mammography alone, BSGI alone, and mammography plus BSGI from the study by Rhodes et al, as well as lifetime estimates of radiation-induced cancer mortality for mammography and BSGI on the basis of the Biologic Effects of Ionizing Radiation VII report, the benefit-to-radiation risk ratios of mammography alone, BSGI alone, and mammography plus BSGI performed annually over 10-year age intervals from ages 40 to 79 years are estimated. Results The benefit-to-radiation risk ratio is estimated to be 13 for women who are 40-49 years old and are screened with mammography, a figure that approximately doubles for each subsequent 10-year age interval up to 70-79 years old. For low-dose BSGI, annual screening benefit-to-radiation risk ratios are estimated to be 5 for women 40-49 years old and to double by age 70-79 years, while mammography plus BSGI has benefit-to-radiation risk ratios similar to those of BSGI alone. There are wide ranges for all of these estimates. Conclusion While lower dose (300 MBq) BSGI has estimated benefit-to-radiation risk ratios well in excess of 1 for screening of asymptomatic women with dense breasts who are 40 years old and older, it does not match the benefit-to-radiation risk ratio of screening mammography. ^© RSNA, 2016.

INDIVIDUALISED CALCULATION OF TISSUE IMPARTED ENERGY IN BREAST TOMOSYNTHESIS

The imparted energy to the glandular tissue in the breast (glandular imparted energy, GIE) is proposed for an improved assessment of the individual radiation-induced risk resulting from X-ray breast imaging. GIE is computed from an estimation of the quantity and localisation of glandular tissue in the breast. After a digital breast tomosynthesis (DBT) acquisition, the volumetric glandular content (volumetric breast density, VBD) is computed from the central X-ray projection. The glandular tissue distribution is determined by labelling the DBT voxels to ensure the conservation of the VBD. Finally, the GIE is calculated by Monte Carlo computation on the resulting tissue-labelled DBT volume. For verification, the method was applied to 10 breast-shaped digital phantoms made of different glandular spheres in an adipose background, and to a digital anthropomorphic phantom. Results were compared to direct GIE computations on the phantoms considered as 'ground-truth'. The major limitations in accuracy are those of DBT, in particular the limited z-resolution. However, for most phantoms, the results can be considered as acceptable.

Radiation doses received in the United Kingdom breast screening programme in 2010 to 2012

OBJECTIVES

To review the radiation doses received by women attending the UK breast-screening programme between 2010 and 2012. To compare doses with previous years and to quantify the impact on dose of changing from analogue to digital imaging and to analyse doses by type of imaging system.

METHODS

Measurements of doses to samples of about 50-100 women attending for screening were collected across the whole of the UK breast-screening programme.

RESULTS

Data were collected for 87,122 exposures, using 449 X-ray sets, for 25,408 women. The average mean glandular dose (MGD) was 1.79 mGy for mediolateral oblique images and 1.58 mGy for craniocaudal images. The average MGD per two-view examination was 4.01 mGy for film-screen imaging and 3.03 mGy for direct digital radiography (DR) and 4.69 mGy for computed radiography.

CONCLUSION

The MGD to women attending breast screening has been reduced on average by about 25% where DR systems have replaced film-screen systems. The dose reduction was greatest for breasts with the largest compressed thickness. There are large variations in dose between the different models of DR system provided by different manufacturers. There should be further work to ensure that all DR systems are operated at the optimal dose level to ensure the best cancer detection while balancing the detriment caused by using radiation.

ADVANCES IN KNOWLEDGE

Changes in the radiation dose in breast screening over time have been determined. Specifically, the impact on radiation dose of introducing different types of DR and computed radiography system into breast screening has been quantified.

Average glandular dose in digital mammography and digital breast tomosynthesis: comparison of phantom and patient data

For the evaluation of the average glandular dose (AGD) in digital mammography (DM) and digital breast tomosynthesis (DBT) phantoms simulating standard model breasts are used. These phantoms consist of slabs of polymethyl methacrylate (PMMA) or a combination of PMMA and polyethylene (PE). In the last decades the automatic exposure control (AEC) increased in complexity and became more sensitive to (local) differences in breast composition. The question is how well the AGD estimated using these simple dosimetry phantoms agrees with the average patient AGD. In this study the AGDs for both dosimetry phantoms and for patients have been evaluated for 5 different x-ray systems in DM and DBT modes. It was found that the ratios between patient and phantom AGD did not differ considerably using both dosimetry phantoms. These ratios averaged over all breast thicknesses were 1.14 and 1.15 for the PMMA and PMMA-PE dosimetry phantoms respectively in DM mode and 1.00 and 1.02 in the DBT mode. These ratios were deemed to be sufficiently close to unity to be suitable for dosimetry evaluation in quality control procedures. However care should be taken when comparing systems for DM and DBT since depending on the AEC operation, ratios for particular breast thicknesses may differ substantially (0.83-1.96). Although the predictions of both phantoms are similar we advise the use of PMMA  +  PE slabs for both DM and DBT to harmonize dosimetry protocols and avoid any potential issues with the use of spacers with the PMMA phantoms.

Evaluation of exposure in mammography: limitations of average glandular dose and proposal of a new quantity

The radiation risk in mammography is traditionally evaluated using the average glandular dose. This quantity for the average breast has proven to be useful for population statistics and to compare exposure techniques and systems. However it is not indicating the individual radiation risk based on the individual glandular amount and distribution. Simulations of exposures were performed for six appropriate virtual phantoms with varying glandular amount and distribution. The individualised average glandular dose (iAGD), i.e. the individual glandular absorbed energy divided by the mass of the gland, and the glandular imparted energy (GIE), i.e. the glandular absorbed energy, were computed. Both quantities were evaluated for their capability to take into account the glandular amount and distribution. As expected, the results have demonstrated that iAGD reflects only the distribution, while GIE reflects both the glandular amount and distribution. Therefore GIE is a good candidate for individual radiation risk assessment.

Radiation dosimetry in digital breast tomosynthesis: report of AAPM Tomosynthesis Subcommittee Task Group 223

The radiation dose involved in any medical imaging modality that uses ionizing radiation needs to be well understood by the medical physics and clinical community. This is especially true of screening modalities. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Therefore, it is important that the medical physics community have the required information to be able to understand, estimate, and communicate the radiation dose levels involved in breast tomosynthesis imaging. For this purpose, the American Association of Physicists in Medicine Task Group 223 on Dosimetry in Tomosynthesis Imaging has prepared this report that discusses dosimetry in breast imaging in general, and describes a methodology and provides the data necessary to estimate mean breast glandular dose from a tomosynthesis acquisition. In an effort to maximize familiarity with the procedures and data provided in this Report, the methodology to perform the dose estimation in DBT is based as much as possible on that used in mammography dose estimation.

Dose assessment in contrast enhanced digital mammography using simple phantoms simulating standard model breasts

Slabs of polymethyl methacrylate (PMMA) or a combination of PMMA and polyethylene (PE) slabs are used to simulate standard model breasts for the evaluation of the average glandular dose (AGD) in digital mammography (DM) and digital breast tomosynthesis (DBT). These phantoms are optimized for the energy spectra used in DM and DBT, which normally have a lower average energy than used in contrast enhanced digital mammography (CEDM). In this study we have investigated whether these phantoms can be used for the evaluation of AGD with the high energy x-ray spectra used in CEDM. For this purpose the calculated values of the incident air kerma for dosimetry phantoms and standard model breasts were compared in a zero degree projection with the use of an anti scatter grid. It was found that the difference in incident air kerma compared to standard model breasts ranges between -10% to +4% for PMMA slabs and between 6% and 15% for PMMA-PE slabs. The estimated systematic error in the measured AGD for both sets of phantoms were considered to be sufficiently small for the evaluation of AGD in quality control procedures for CEDM. However, the systematic error can be substantial if AGD values from different phantoms are compared.

Estimation of mean glandular dose for contrast enhanced digital mammography: factors for use with the UK, European and IAEA breast dosimetry protocols

The UK, European and IAEA protocols for breast dosimetry in mammography use tabulations of conversion factors, which relate measurements of incident air kerma to the mean glandular dose to the breast. To supplement the existing tabulations, a Monte Carlo computer program has been used to calculate conversion factors for the high-energy spectra used for contrast enhanced digital mammography. The calculations were made for the x-ray spectra from a tungsten target (tube voltage range 40-50 kV) filtered by 0.28, 0.30 and 0.32 mm of copper, and from molybdenum and rhodium targets (tube voltage range 40-49 kV), each filtered by 0.30 mm of copper. The g-factors for all of these spectra were plotted for each breast thickness as a function of half value layer (HVL) and were found to lie on smooth curves within 0.3%. These reflect the fact that the characteristic x-rays present in the spectra from molybdenum and rhodium are heavily filtered and all the spectra are essentially Bremsstrahlung. As a consequence, the s-factor previously used in the dosimetry protocols to adjust for different target/filter combinations can be taken as unity for all of the spectra considered. Tables of g-factors and c-factors are provided for breast thicknesses in the range 20-110 mm and HVLs in the range 2.4-3.6 mm of aluminium. The tables of c-factors are given for breast glandularities in the range 0.1%-100% and for typical glandularities for women in the age bands 40-49 and 50-64 attending the UK national breast screening programme.

Objective models of compressed breast shapes undergoing mammography

PURPOSE

To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes.

METHODS

An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE).

RESULTS

The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six-component model was also used to generate CC and MLO view mammogram breast shapes, using the mean PCA parameter values of these distributions and randomly generated values based on the fitted Gaussian distributions, which resemble clinically encountered breasts. A spreadsheet with the data necessary to apply this model is provided as the supplementary material.

CONCLUSIONS

Our PCA models of breast shapes in both mammographic views successfully reproduce analyzed breast shapes and generate new clinically relevant shapes. This work can aid in research applications which incorporate breast shape modeling, such as x-ray scatter correction, dosimetry, and image registration.

Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry

PURPOSE

To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation.

METHODS

Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio-caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x-ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x-ray spectra were used, corresponding to the x-ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared.

RESULTS

For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Test p = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution.

CONCLUSIONS

The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x-ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x-ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further work is required to better characterize this overestimation and potentially develop new metrics or correction factors to better estimate the true glandular dose to breasts undergoing imaging with ionizing radiation.

Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm

PURPOSE

We present a novel algorithm for computer simulation of breast anatomy for generation of anthropomorphic software breast phantoms. A realistic breast simulation is necessary for preclinical validation of volumetric imaging modalities.

METHODS

The anthropomorphic software breast phantom simulates the skin, regions of adipose and fibroglandular tissue, and the matrix of Cooper's ligaments and adipose compartments. The adipose compartments are simulated using a seeded region-growing algorithm; compartments are grown from a set of seed points with specific orientation and growing speed. The resulting adipose compartments vary in shape and size similar to real breasts; the adipose region has a compact coverage by adipose compartments of various sizes, while the fibroglandular region has fewer, more widely separated adipose compartments. Simulation parameters can be selected to cover the breadth of variations in breast anatomy observed clinically.

RESULTS

When simulating breasts of the same glandularity with different numbers of adipose compartments, the average compartment volume was proportional to the phantom size and inversely proportional to the number of simulated compartments. The use of the software phantom in clinical image simulation is illustrated by synthetic digital breast tomosynthesis images of the phantom. The proposed phantom design was capable of simulating breasts of different size, glandularity, and adipose compartment distribution. The region-growing approach allowed us to simulate adipose compartments with various size and shape. Qualitatively, simulated x-ray projections of the phantoms, generated using the proposed algorithm, have a more realistic appearance compared to previous versions of the phantom.

CONCLUSIONS

A new algorithm for computer simulation of breast anatomy has been proposed that improved the realism of the anthropomorphic software breast phantom.

Evaluation of the absorbed dose to the breast using radiochromic film in a dedicated CT mammotomography system employing a quasi-monochromatic x-ray beam

PURPOSE

A dual modality SPECT-CT prototype system dedicated to uncompressed breast imaging (mammotomography) has been developed. The computed tomography subsystem incorporates an ultrathick K-edge filtration technique producing a quasi-monochromatic x-ray cone beam that optimizes the dose efficiency of the system for lesion imaging in an uncompressed breast. Here, the absorbed dose in various geometric phantoms and in an uncompressed and pendant cadaveric breast using a normal tomographic cone beam imaging protocol is characterized using both thermoluminescent dosimeter (TLD) measurements and ionization chamber-calibrated radiochromic film.

METHODS

Initially, two geometric phantoms and an anthropomorphic breast phantom are filled in turn with oil and water to simulate the dose to objects that mimic various breast shapes having effective density bounds of 100% fatty and glandular breast compositions, respectively. Ultimately, an excised human cadaver breast is tomographically scanned using the normal tomographic imaging protocol, and the dose to the breast tissue is evaluated and compared to the earlier phantom-based measurements.

RESULTS

Measured trends in dose distribution across all breast geometric and anthropomorphic phantom volumes indicate lower doses in the medial breast and more proximal to the chest wall, with consequently higher doses near the lateral peripheries and nipple regions. Measured doses to the oil-filled phantoms are consistently lower across all volume shapes due to the reduced mass energy-absorption coefficient of oil relative to water. The mean measured dose to the breast cadaver, composed of adipose and glandular tissues, was measured to be 4.2 mGy compared to a mean whole-breast dose of 3.8 and 4.5 mGy for the oil- and water-filled anthropomorphic breast phantoms, respectively.

CONCLUSIONS

Assuming rotational symmetry due to the tomographic acquisition exposures, these results characterize the 3D dose distributions in an uncompressed human breast tissue volume for this dedicated breast imaging device and illustrate advantages of using the novel ultrathick K-edge filtered beam to minimize the dose to the breast during fully-3D imaging.

Radiation doses in cone-beam breast computed tomography: a Monte Carlo simulation study

PURPOSE

In this article, we describe a method to estimate the spatial dose variation, average dose and mean glandular dose (MGD) for a real breast using Monte Carlo simulation based on cone beam breast computed tomography (CBBCT) images. We present and discuss the dose estimation results for 19 mastectomy breast specimens, 4 homogeneous breast models, 6 ellipsoidal phantoms, and 6 cylindrical phantoms.

METHODS

To validate the Monte Carlo method for dose estimation in CBBCT, we compared the Monte Carlo dose estimates with the thermoluminescent dosimeter measurements at various radial positions in two polycarbonate cylinders (11- and 15-cm in diameter). Cone-beam computed tomography (CBCT) images of 19 mastectomy breast specimens, obtained with a bench-top experimental scanner, were segmented and used to construct 19 structured breast models. Monte Carlo simulation of CBBCT with these models was performed and used to estimate the point doses, average doses, and mean glandular doses for unit open air exposure at the iso-center. Mass based glandularity values were computed and used to investigate their effects on the average doses as well as the mean glandular doses. Average doses for 4 homogeneous breast models were estimated and compared to those of the corresponding structured breast models to investigate the effect of tissue structures. Average doses for ellipsoidal and cylindrical digital phantoms of identical diameter and height were also estimated for various glandularity values and compared with those for the structured breast models.

RESULTS

The absorbed dose maps for structured breast models show that doses in the glandular tissue were higher than those in the nearby adipose tissue. Estimated average doses for the homogeneous breast models were almost identical to those for the structured breast models (p=1). Normalized average doses estimated for the ellipsoidal phantoms were similar to those for the structured breast models (root mean square (rms) percentage difference = 1.7%; p = 0.01), whereas those for the cylindrical phantoms were significantly lower (rms percentage difference = 7.7%; p < 0.01). Normalized MGDs were found to decrease with increasing glandularity.

CONCLUSIONS

Our results indicate that it is sufficient to use homogeneous breast models derived from CBCT generated structured breast models to estimate the average dose. This investigation also shows that ellipsoidal digital phantoms of similar dimensions (diameter and height) and glandularity to actual breasts may be used to represent a real breast to estimate the average breast dose with Monte Carlo simulation. We have also successfully demonstrated the use of structured breast models to estimate the true MGDs and shown that the normalized MGDs decreased with the glandularity as previously reported by other researchers for CBBCT or mammography.

An anthropomorphic phantom for quantitative evaluation of breast MRI

PURPOSE

In this study, the authors aim to develop a physical, tissue-mimicking phantom for quantitative evaluation of breast MRI protocols. The objective of this phantom is to address the need for improved standardization in breast MRI and provide a platform for evaluating the influence of image protocol parameters on lesion detection and discrimination. Quantitative comparisons between patient and phantom image properties are presented.

METHODS

The phantom is constructed using a mixture of lard and egg whites, resulting in a random structure with separate adipose- and glandular-mimicking components. T1 and T2 relaxation times of the lard and egg components of the phantom were estimated at 1.5 T from inversion recovery and spin-echo scans, respectively, using maximum-likelihood methods. The image structure was examined quantitatively by calculating and comparing spatial covariance matrices of phantom and patient images. A static, enhancing lesion was introduced by creating a hollow mold with stereolithography and filling it with a gadolinium-doped water solution.

RESULTS

Measured phantom relaxation values fall within 2 standard errors of human values from the literature and are reasonably stable over 9 months of testing. Comparison of the covariance matrices of phantom and patient data demonstrates that the phantom and patient data have similar image structure. Their covariance matrices are the same to within error bars in the anterior-posterior direction and to within about two error bars in the right-left direction. The signal from the phantom's adipose-mimicking material can be suppressed using active fat-suppression protocols. A static, enhancing lesion can also be included with the ability to change morphology and contrast agent concentration.

CONCLUSIONS

The authors have constructed a phantom and demonstrated its ability to mimic human breast images in terms of key physical properties that are relevant to breast MRI. This phantom provides a platform for the optimization and standardization of breast MRI imaging protocols for lesion detection and characterization.

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: application for mammography

PURPOSE

This work presents an improved algorithm for the generation of 3D breast software phantoms and its evaluation for mammography.

METHODS

The improved methodology has evolved from a previously presented 3D noncompressed breast modeling method used for the creation of breast models of different size, shape, and composition. The breast phantom is composed of breast surface, duct system and terminal ductal lobular units, Cooper's ligaments, lymphatic and blood vessel systems, pectoral muscle, skin, 3D mammographic background texture, and breast abnormalities. The key improvement is the development of a new algorithm for 3D mammographic texture generation. Simulated images of the enhanced 3D breast model without lesions were produced by simulating mammographic image acquisition and were evaluated subjectively and quantitatively. For evaluation purposes, a database with regions of interest taken from simulated and real mammograms was created. Four experienced radiologists participated in a visual subjective evaluation trial, as they judged the quality of the simulated mammograms, using the new algorithm compared to mammograms, obtained with the old modeling approach. In addition, extensive quantitative evaluation included power spectral analysis and calculation of fractal dimension, skewness, and kurtosis of simulated and real mammograms from the database.

RESULTS

The results from the subjective evaluation strongly suggest that the new methodology for mammographic breast texture creates improved breast models compared to the old approach. Calculated parameters on simulated images such as beta exponent deducted from the power law spectral analysis and fractal dimension are similar to those calculated on real mammograms. The results for the kurtosis and skewness are also in good coincidence with those calculated from clinical images. Comparison with similar calculations published in the literature showed good agreement in the majority of cases.

CONCLUSIONS

The improved methodology generated breast models with increased realism compared to the older model as shown in evaluations of simulated images by experienced radiologists. It is anticipated that the realism will be further improved using an advanced image simulator so that simulated images may be used in feasibility studies in mammography.

Estimation of mean glandular dose for breast tomosynthesis: factors for use with the UK, European and IAEA breast dosimetry protocols

A formalism is proposed for the estimation of mean glandular dose for breast tomosynthesis, which is a simple extension of the UK, European and IAEA protocols for dosimetry in conventional projection mammography. The formalism introduces t-factors for the calculation of breast dose from a single projection and T-factors for a complete exposure series. Monte Carlo calculations of t-factors have been made for an imaging geometry with full-field irradiation of the breast for a wide range of x-ray spectra, breast sizes and glandularities. The t-factors show little dependence on breast glandularity and tables are provided as a function of projection angle and breast thickness, which may be used for all x-ray spectra simulated. The T-factors for this geometry depend upon the choice of projection angles and weights per projection, but various example calculations gave values in the range 0.93-1.00. T-factors are also provided for the Sectra tomosynthesis system, which employs a scanned narrow-beam imaging geometry. In this quite different configuration, the factor (denoted T(S)) shows an important dependence on breast thickness, varying between 0.98 and 0.76 for 20 and 110 mm thick breasts, respectively. Additional data are given to extend the current tabulations of g-, c- and s-factors used for dosimetry of conventional 2D mammography.

Estudo comparativo de dosimetria computacional entre modelos homogêneos e um modelo voxel em mamografia: uma discussão de aplicações em testes de constância e cálculo de dose glandular em pacientes

OBJETIVO: Comparar dados de dosimetria e fluência de fótons entre diferentes modelos de mama, discutindo as aplicações em testes de constância e estudos dosimétricos aplicados à mamografia. MATERIAIS E MÉTODOS: Foram simulados diferentes modelos homogêneos e um modelo antropomórfico de mama tipo voxel, sendo contabilizadas: a dose total absorvida no modelo, a dose absorvida pelo tecido glandular/material equivalente, e a dose absorvida e a fluência de fótons em diferentes profundidades dos modelos. Uma câmara de ionização simulada coletou o kerma de entrada na pele. As combinações alvo-filtro estudadas foram Mo-30Mo e Mo-25Rh, para diferentes potenciais aceleradores de 26 kVp até 34 kVp. RESULTADOS: A dose glandular normalizada, comparada ao modelo voxel, resultou em diferenças entre -15% até -21% para RMI, -10% para PhantomMama e 10% para os modelos Barts e Keithley. A variação dos valores da camada semirredutora entre modelos foi geralmente inferior a 10% para todos os volumes sensíveis. CONCLUSÃO: Para avaliar a dose glandular normalizada e a dose glandular, em mamas médias, recomenda-se o modelo de Dance. Os modelos homogêneos devem ser utilizados para realizar testes de constância em dosimetria, mas eles não são indicados para estimar a dosimetria em pacientes reais

Introducing DeBRa: a detailed breast model for radiological studies

Currently, x-ray mammography is the method of choice in breast cancer screening programmes. As the mammography technology moves from 2D imaging modalities to 3D, conventional computational phantoms do not have sufficient detail to support the studies of these advanced imaging systems. Studies of these 3D imaging systems call for a realistic and sophisticated computational model of the breast. DeBRa (Detailed Breast model for Radiological studies) is the most advanced, detailed, 3D computational model of the breast developed recently for breast imaging studies. A DeBRa phantom can be constructed to model a compressed breast, as in film/screen, digital mammography and digital breast tomosynthesis studies, or a non-compressed breast as in positron emission mammography and breast CT studies. Both the cranial-caudal and mediolateral oblique views can be modelled. The anatomical details inside the phantom include the lactiferous duct system, the Cooper ligaments and the pectoral muscle. The fibroglandular tissues are also modelled realistically. In addition, abnormalities such as microcalcifications, irregular tumours and spiculated tumours are inserted into the phantom. Existing sophisticated breast models require specialized simulation codes. Unlike its predecessors, DeBRa has elemental compositions and densities incorporated into its voxels including those of the explicitly modelled anatomical structures and the noise-like fibroglandular tissues. The voxel dimensions are specified as needed by any study and the microcalcifications are embedded into the voxels so that the microcalcification sizes are not limited by the voxel dimensions. Therefore, DeBRa works with general-purpose Monte Carlo codes. Furthermore, general-purpose Monte Carlo codes allow different types of imaging modalities and detector characteristics to be simulated with ease. DeBRa is a versatile and multipurpose model specifically designed for both x-ray and gamma-ray imaging studies.