The effect of skin thickness determined using breast CT on mammographic dosimetry

In-line spectroscopy for iodine quantification in dynamic contrast-enhanced dedicated breast CT

BACKGROUND

In 4D dynamic contrast-enhanced dedicated breast computed tomography (4D DCE-bCT), the functional properties of the breast will be characterized by monitoring the uptake and washout of iodine-based contrast agents over time. This information could be valuable in breast cancer treatment. However, prior to clinical implementation, it is crucial to validate the quantitative estimates of iodine concentrations at each time point during acquisition.

PURPOSE

To develop an in-line spectroscopy system capable of measuring iodine concentrations in a dynamic x-ray breast phantom in real-time.

METHODS

Potassium iodide served as the contrast agent. The system was set-up at both the entrance and exit of the phantom. It comprises a fiber-coupled green LED and collimator, which together ensure that a parallel beam passes through the sample holder. Transmitted light is captured by a collimator on the opposite side and directed through a fiber optic cable to a photodetector for intensity measurement. The relationship between 13 iodine concentrations (0-6 mg I/mL) and light transmission was tested, and the system's repeatability and accuracy were determined.

RESULTS

The system exhibited a strong correlation between iodine concentration and transmission values, achieving a root-mean-square error of 0.007. The repeated measurements had relative standard deviations of 0.04% and 0.1% for repeated water measurements at the phantom's entrance and exit, respectively. Furthermore, the accuracy measurements gave a mean error of fitting of 0.008 (± 0.07) mg I/mL.

CONCLUSION

The in-line spectroscopy system can effectively monitor iodine concentrations in a dynamic breast phantom, providing a reliable method for quantitative validation of 4D DCE-bCT.

Construction of multi-component finite element model to predict biomechanical behaviour of breasts during running and quantification of the stiffness impact of internal structure

This study aims to investigate the biomechanical behaviour and the stiffness impact of the breast internal components during running. To achieve this, a novel nonlinear multi-component dynamic finite element method (FEM) has been established, which uses experimental data obtained via 4D scanning technology and a motion capture system. The data are used to construct a geometric model that comprises the rigid body, layers of soft tissues, skin, pectoralis major muscle, fat, ligaments and glandular tissues. The traditional point-to-point method has a relative mean absolute error of less than 7.92% while the latest surface-to-surface method has an average Euclidean distance (d) of 7.05 mm, validating the simulated results. After simulating the motion of the different components of the breasts, the displacement analysis confirms that when the motion reaches the moment of largest displacement, the displacement of the breast components is proportional to their distance from the chest wall. A biomechanical analysis indicates that the stress sustained by the breast components in ascending order is the glandular tissues, pectoralis major muscle, adipose tissues, and ligaments. The ligaments provide the primary support during motion, followed by the pectoralis major muscle. In addition, specific stress points of the breast components are identified. The stiffness impact experiment indicates that compared with ligaments, the change of glandular tissue stiffness had a slightly more obvious effect on the breast surface. The findings serve as a valuable reference for the medical field and sports bra industry to enhance breast protection during motion.

Breast density quantification in dual-energy mammography using virtual anthropomorphic phantoms

PURPOSE

Breast density is a significant risk factor for breast cancer and can impact the sensitivity of screening mammography. Area-based breast density measurements may not provide an accurate representation of the tissue distribution, therefore volumetric breast density (VBD) measurements are preferred. Dual-energy mammography enables volumetric measurements without additional assumptions about breast shape. In this work we evaluated the performance of a dual-energy decomposition technique for determining VBD by applying it to virtual anthropomorphic phantoms.

METHODS

The dual-energy decomposition formalism was used to quantify VBD on simulated dual-energy images of anthropomorphic virtual phantoms with known tissue distributions. We simulated 150 phantoms with volumes ranging from 50 to 709 mL and VBD ranging from 15% to 60%. Using these results, we validated a correction for the presence of skin and assessed the method's intrinsic bias and variability. As a proof of concept, the method was applied to 14 sets of clinical dual-energy images, and the resulting breast densities were compared to magnetic resonance imaging (MRI) measurements.

RESULTS

Virtual phantom VBD measurements exhibited a strong correlation (Pearson'sr > 0.95 $r > 0.95$ ) with nominal values. The proposed skin correction eliminated the variability due to breast size and reduced the bias in VBD to a constant value of -2%. Disagreement between clinical VBD measurements using MRI and dual-energy mammography was under 10%, and the difference in the distributions was statistically non-significant. VBD measurements in both modalities had a moderate correlation (Spearman'sρ $\rho \ $ = 0.68).

CONCLUSIONS

Our results in virtual phantoms indicate that the material decomposition method can produce accurate VBD measurements if the presence of a third material (skin) is considered. The results from our proof of concept showed agreement between MRI and dual-energy mammography VBD. Assessment of VBD using dual-energy images could provide complementary information in dual-energy mammography and tomosynthesis examinations.

Maximizing microcalcification detectability in low-dose dedicated cone-beam breast CT: parallel cascades-based theoretical analysis

Purpose

We aim to determine the combination of X-ray spectrum and detector scintillator thickness that maximizes the detectability of microcalcification clusters in dedicated cone-beam breast CT.

Approach

A cascaded linear system analysis was implemented in the spatial frequency domain and was used to determine the detectability index using numerical observers for the imaging task of detecting a microcalcification cluster with 0.17 mm diameter calcium carbonate spheres. The analysis considered a thallium-doped cesium iodide scintillator coupled to a complementary metal-oxide semiconductor detector and an analytical filtered-back-projection reconstruction algorithm. Independent system parameters considered were the scintillator thickness, applied X-ray tube voltage, and X-ray beam filtration. The combination of these parameters that maximized the detectability index was considered optimal.

Results

Prewhitening, nonprewhitening, and nonprewhitening with eye filter numerical observers indicate that the combination of 0.525 to 0.6 mm thick scintillator, 70 kV, and 0.25 to 0.4 mm added copper filtration maximized the detectability index at a mean glandular dose (MGD) of 4.5 mGy.

Conclusion

Using parallel cascade systems' analysis, the combination of parameters that could maximize the detection of microcalcifications was identified. The analysis indicates that a harder beam than that used in current practice may be beneficial for the task of detecting microcalcifications at an MGD suitable for breast cancer screening.

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.

Joint AAPM Task Group 282/EFOMP Working Group Report: Breast dosimetry for standard and contrast-enhanced mammography and breast tomosynthesis

Currently, there are multiple breast dosimetry estimation methods for mammography and its variants in use throughout the world. This fact alone introduces uncertainty, since it is often impossible to distinguish which model is internally used by a specific imaging system. In addition, all current models are hampered by various limitations, in terms of overly simplified models of the breast and its composition, as well as simplistic models of the imaging system. Many of these simplifications were necessary, for the most part, due to the need to limit the computational cost of obtaining the required dose conversion coefficients decades ago, when these models were first implemented. With the advancements in computational power, and to address most of the known limitations of previous breast dosimetry methods, a new breast dosimetry method, based on new breast models, has been developed, implemented, and tested. This model, developed jointly by the American Association of Physicists in Medicine and the European Federation for Organizations of Medical Physics, is applicable to standard mammography, digital breast tomosynthesis, and their contrast-enhanced variants. In addition, it includes models of the breast in both the cranio-caudal and the medio-lateral oblique views. Special emphasis was placed on the breast and system models used being based on evidence, either by analysis of large sets of patient data or by performing measurements on imaging devices from a range of manufacturers. Due to the vast number of dose conversion coefficients resulting from the developed model, and the relative complexity of the calculations needed to apply it, a software program has been made available for download or online use, free of charge, to apply the developed breast dosimetry method. The program is available for download or it can be used directly online. A separate User's Guide is provided with the software.

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning

Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast tissue, such as glandular tissue, fat, and lesions, differ in sound speed. Given a constant sound speed assumption, these differences can degrade the quality of reconstructed images via phase aberration. Sound speed images can be a powerful tool for improving image quality and identifying diseases if properly estimated. To this end, we propose a supervised deep-learning approach for sound speed estimation from analytic ultrasound signals. We develop a large-scale simulated ultrasound dataset that generates representative breast tissue samples by modeling breast gland, skin, and lesions with varying echogenicity and sound speed. We adopt a fully convolutional neural network architecture trained on a simulated dataset to produce an estimated sound speed map. The simulated tissue is interrogated with a plane wave transmit sequence, and the complex-value reconstructed images are used as input for the convolutional network. The network is trained on the sound speed distribution map of the simulated data, and the trained model can estimate sound speed given reconstructed pulse-echo signals. We further incorporate thermal noise augmentation during training to enhance model robustness to artifacts found in real ultrasound data. To highlight the ability of our model to provide accurate sound speed estimations, we evaluate it on simulated, phantom, and in-vivo breast ultrasound data.

Phantoms for evaluating the impact of skin pigmentation on photoacoustic imaging and oximetry performance

Recent reports have raised concerns of potential racial disparities in performance of optical oximetry technologies. To investigate how variable epidermal melanin content affects performance of photoacoustic imaging (PAI) devices, we developed plastisol phantoms combining swappable skin-mimicking layers with a breast phantom containing either India ink or blood adjusted to 50-100% SO2 using sodium dithionite. Increasing skin pigmentation decreased maximum imaging depth by up to 25%, enhanced image clutter, and increased root-mean-square error in SO2 from 8.0 to 17.6% due to signal attenuation and spectral coloring effects. This phantom tool can aid in evaluating PAI device robustness to ensure high performance in all patients.

Dedicated cone-beam breast CT: Data acquisition strategies based on projection angle-dependent normalized glandular dose coefficients

BACKGROUND

Dedicated cone-beam breast computed tomography (CBBCT) using short-scan acquisition is being actively investigated to potentially reduce the radiation dose to the breast. This would require determining the optimal x-ray source trajectory for such short-scan acquisition.

PURPOSE

To quantify the projection angle-dependent normalized glandular dose coefficient (D g N C T $Dg{N^{CT}}$ ) in CBBCT, referred to as angularD g N C T $Dg{N^{CT}}$ , so that the x-ray ray source trajectory that minimizes the radiation dose to the breast for short-scan acquisition can be determined.

MATERIALS AND METHODS

A cohort of 75 CBBCT clinical datasets was segmented and used to generate three breast models - (I) patient-specific breast with heterogeneous fibroglandular tissue distribution and real breast shape, (II) patient-specific breast shape with homogeneous tissue distribution and matched fibroglandular weight fraction, and (III) homogeneous semi-ellipsoidal breast with patient-specific breast dimensions and matched fibroglandular weight fraction, which corresponds to the breast model used in current radiation dosimetry protocols. For each clinical dataset, the angularD g N C T $Dg{N^{CT}}$ was obtained at 10 discrete angles, spaced 36° apart, for full-scan, circular, x-ray source trajectory from Monte Carlo simulations. Model III is used for validating the Monte Carlo simulation results. Models II and III are used to determine if breast shape contributes to the observed trends in angularD g N C T $Dg{N^{CT}}$ . A geometry-based theory in conjunction with center-of-mass (C O M $COM$ ) based distribution analysis is used to explain the projection angle-dependent variation in angularD g N C T $Dg{N^{CT}}$ .

RESULTS

The theoretical model predicted that the angularD g N C T $Dg{N^{CT}}$ will follow a sinusoidal pattern and the amplitude of the sinusoid increases when the center-of-mass of fibroglandular tissue (C O M f $CO{M_f}$ ) is farther from the center-of-mass of the breast (C O M b $CO{M_b}$ ). It also predicted that the angularD g N C T $Dg{N^{CT}}$ will be minimized at x-ray source positions complementary to theC O M f $CO{M_f}$ . TheC O M f $CO{M_f}$ was superior to theC O M b $CO{M_b}$ in 80% (60/75) of the breasts. From Monte Carlo simulations and for homogeneous breasts (models II and III), the deviation in breast shape from a semi-ellipsoid had minimal effect on angularD g N C T $Dg{N^{CT}}$ and showed less than 4% variation. From Monte Carlo simulations and for model I, as predicted by our theory, the angularD g N C T $Dg{N^{CT}}$ followed a sinusoidal pattern with maxima and minima at x-ray source positions superior and inferior to the breast, respectively. For model I, the projection angle-dependent variation in angularD g N C T $Dg{N^{CT}}$ was 16.4%.

CONCLUSION

The heterogeneous tissue distribution affected the angularD g N C T $Dg{N^{CT}}$ more than the breast shape. For model I, the angularD g N C T $Dg{N^{CT}}$ was lowest when the x-ray source was inferior to the breast. Hence, for short-scan CBBCT acquisition withC O M b $CO{M_b}$ aligned with axis-of-rotation, an x-ray source trajectory inferior to the breast is preferable and such an acquisition spanning 205° can potentially reduce the mean glandular dose by up to 52%.

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.

Breast dosimetry in alternative X-ray-based imaging modalities used in current clinical practices

In X-ray breast imaging, Digital Mammography (DM) and Digital Breast Tomosynthesis (DBT), are the standard and largely used techniques, both for diagnostic and screening purposes. Other techniques, such as dedicated Breast Computed Tomography (BCT) and Contrast Enhanced Mammography (CEM) have been developed as an alternative or a complementary technique to the established ones. The performance of these imaging techniques is being continuously assessed to improve the image quality and to reduce the radiation dose. These imaging modalities are predominantly used in the diagnostic setting to resolve incomplete or indeterminate findings detected with conventional screening examinations and could potentially be used either as an adjunct or as a primary screening tool in select populations, such as for women with dense breasts. The aim of this review is to describe the radiation dosimetry for these imaging techniques, and to compare the mean glandular dose with standard breast imaging modalities, such as DM and DBT.

In Vivo Measurements of the Bulk Ultrasonic Attenuation Coefficient of Breast Tissue Using a Novel Phase-Insensitive Receiver

This study describes the first in vivo acoustic attenuation measurements of breast tissue undertaken using a novel phase-insensitive detection technique employing a differential pyroelectric sensor. The operation of the sensor is thermal in nature, with its output signal being dictated by the acoustic power integrated over its surface. The particularly novel feature of the sensor lies in its differential principle of operation, which significantly enhances its immunity to background acoustic and vibration noise. A large area variant of the sensor was used to detect ultrasonic energy generated by an array of 14 discrete 3.2-MHz plane piston transducers, transmitted through pendent breasts in water. The transduction and reception capability represent key parts of a prototype Quantitative Ultrasound Computed Tomography Test Facility developed at the National Physical Laboratory to study the efficacy of phase-insensitive ultrasound computed tomography of breast phantoms containing a range of appropriate inclusions, in particular, the measurement uncertainties associated with quantitative reconstructions of the acoustic attenuation coefficient. For this study, attenuation coefficient measurements were made using 1-D projections on 12 nominally healthy study volunteers, whose age ranged from 19 to 65 years. Averaged or bulk attenuation coefficient values were generated in the range 1.7-4.6 dBcm ^-1 at 3.2 MHz and have been compared with existing literature, derived from in vivo and ex vivo studies. Results are encouraging and indicate that the relatively simple technique could be applied as a robust method for assessing the properties of breast tissue, particularly the balance of fatty (adipose) and fibroglandular components.

Patient-derived heterogeneous breast phantoms for advanced dosimetry in mammography and tomosynthesis

Background

Understanding the magnitude and variability of the radiation dose absorbed by the breast fibroglandular tissue during mammography and digital breast tomosynthesis (DBT) is of paramount importance to assess risks versus benefits. Although homogeneous breast models have been proposed and used for decades for this purpose, they do not accurately reflect the actual heterogeneous distribution of the fibroglandular tissue in the breast, leading to biases in the estimation of dose from these modalities.

Purpose

To develop and validate a method to generate patient‐derived, heterogeneous digital breast phantoms for breast dosimetry in mammography and DBT.

Methods

The proposed phantoms were developed starting from patient‐based models of compressed breasts, generated for multiple thicknesses and representing the two standard views acquired in mammography and DBT, that is, cranio‐caudal (CC) and medio‐lateral‐oblique (MLO). Internally, the breast phantoms were defined as consisting of an adipose/fibroglandular tissue mixture, with a nonspatially uniform relative concentration. The parenchyma distributions were obtained from a previously described model based on patient breast computed tomography data that underwent simulated compression. Following these distributions, phantoms with any glandular fraction (1%–100%) and breast thickness (12–125 mm) can be generated, for both views. The phantoms were validated, in terms of their accuracy for average normalized glandular dose (D_gN) estimation across samples of patient breasts, using 88 patient‐specific phantoms involving actual patient distribution of the fibroglandular tissue in the breast, and compared to that obtained using a homogeneous model similar to those currently used for breast dosimetry.

Results

The average D_gN estimated for the proposed phantoms was concordant with that absorbed by the patient‐specific phantoms to within 5% (CC) and 4% (MLO). These D_gN estimates were over 30% lower than those estimated with the homogeneous models, which overestimated the average D_gN by 43% (CC), and 32% (MLO) compared to the patient‐specific phantoms.

Conclusions

The developed phantoms can be used for dosimetry simulations to improve the accuracy of dose estimates in mammography and DBT.

Gold-nanoparticle-enriched breast tissue in breast cancer treatment using the INTRABEAM® system: a Monte Carlo study

Using a 50-kV INTRABEAM^® system after breast-conserving surgery, breast skin injury and long treatment time remain the challenging problems when large-size spherical applicators are used. This study has aimed to address these problems using gold (Au) nanoparticles (NPs). For this, surface and isotropic doses were measured using a Gafchromic EBT3 film and a water phantom. The particle propagation code EGSnrc/Epp was used to score the corresponding doses using a geometry similar to that used in the measurements. The simulation was validated using a gamma index of 2%/2 mm acceptance criterion in the gamma analysis. After validation Au-NP-enriched breast tissue was simulated to quantify any breast skin dose reduction and shortening of treatment time. It turned out that the gamma value deduced for validation of the simulation was in an acceptable range (i.e., less than one). For 20 mg-Au/g-breast tissue, the calculated Dose Enhancement Ratio (DER) of the breast skin was 0.412 and 0.414 using applicators with diameters of 1.5 cm and 5 cm, respectively. The corresponding treatment times were shortened by 72.22% and 72.30% at 20 mg-Au/g-breast tissue concentration, respectively. It is concluded that Au-NP-enriched breast tissue shows significant advantages, such as reducing the radiation dose received by the breast skin as well as shortening the treatment time. Additionally, the DERs were not significantly dependent on the size of the applicators.

Mechanical properties of whole-body soft human tissues: a review

The mechanical properties of soft tissues play a key role in studying human injuries and their mitigation strategies. While such properties are indispensable for computational modelling of biological systems, they serve as important references in loading and failure experiments, and also for the development of tissue simulants. To date, experimental studies have measured the mechanical properties of peripheral tissues (e.g. skin)in-vivoand limited internal tissuesex-vivoin cadavers (e.g. brain and the heart). The lack of knowledge on a majority of human tissues inhibit their study for applications ranging from surgical planning, ballistic testing, implantable medical device development, and the assessment of traumatic injuries. The purpose of this work is to overcome such challenges through an extensive review of the literature reporting the mechanical properties of whole-body soft tissues from head to toe. Specifically, the available linear mechanical properties of all human tissues were compiled. Non-linear biomechanical models were also introduced, and the soft human tissues characterized using such models were summarized. The literature gaps identified from this work will help future biomechanical studies on soft human tissue characterization and the development of accurate medical models for the study and mitigation of injuries.

Dosimetry in Digital Breast Tomosynthesis Evaluated by Monte Carlo Technique

ABSTRACT

The influence of the angular deviation of the tube during digital breast tomosynthesis (DBT) acquisition to the dose in the examined breast and in other organs and tissues is not well known. In this work, the Monte Carlo method was used with an adult female virtual anthropomorphic phantom to investigate the impact of this angular variation on the breast dose. The absorbed dose in the examined breast was normalized by the air kerma, which resulted in an absorbed dose coefficient (DT/Kair) for the breast. The absorbed dose in each organ was normalized by the glandular dose in the breast, resulting in the relative organ dose (ROD). An adult female virtual anthropomorphic phantom (FSTA_M50_H50) was incorporated into a scenario containing tomosynthesis equipment with Mo/Mo, Mo/Rh, and W/Rh target/filter combinations and tube voltages of 28 kV. The comparison between the results of the simulations considering digital mammography (DM) and DBT data showed that the DT/Kair values for the examined breast obtained with the DBT parameters were up to 24 times higher than with the DT/Kair obtained with DM parameters. A DT/Kair of 0.97 × 10-1 mGy mGy-1 was obtained in a DBT exam of the right breast. Considering the other organs, the highest ROD values were observed in the thyroid (6.45 × 10-4), eyes (3.87 × 10-4), liver (1.95 × 10-5), and eye lenses (3.21 × 10-3). A variation in the absorbed dose values for the breast and other organs was observed for all projections different from 0°.

Impact of photoelectric cross section data on systematic uncertainties for Monte Carlo breast dosimetry in mammography

Monte Carlo (MC) simulations are employed extensively in breast dosimetry studies. In the energy interval of interest in mammography energy deposition is predominantly caused by the photoelectric effect, and the corresponding cross sections used by the MC codes to model this interaction process have a direct influence on the simulation results. The present work compares two photoelectric cross section databases in order to estimate the systematic uncertainty, related to breast dosimetry, introduced by the choice of cross sections for photoabsorption. The databases with and without the so-called normalization screening correction are denoted as 'renormalized' or 'un-normalized', respectively. The simulations were performed with the PENELOPE/penEasy code system, for a geometry resembling a mammography examination. The mean glandular dose (MGD), incident air kerma (K_air), normalized glandular dose (DgN) and glandular depth-dose (GDD(z)) were scored, for homogeneous breast phantoms, using both databases. The AAPM Report TG-195 case 3 was replicated, and the results were included. Moreover, cases with heterogeneous and anthropomorphic breast phantoms were also addressed. The results simulated with the un-normalized cross sections are in better overall agreement with the TG-195 data than those from the renormalized cross sections; for MGD the largest discrepancies are 0.13(6)% and 0.74(5)%, respectively. The MGD,K_airand DgN values simulated with the two databases show differences that diminish from approximately 10%/3%/6.8% at 8.25 keV down to 1.5%/1.7%/0.4% at 48.75 keV, respectively. For polyenergetic spectra, deviations up to 2.5% were observed. The disagreement between the GDDs simulated with the analyzed databases increases with depth, ranging from -1% near the breast entrance to 4% near the bottom. Thus, the choice of photoelectric cross section database affects the MC simulation results of breast dosimetry and adds a non-negligible systematic uncertainty to the dosimetric quantities used in mammography.

THz Sensing of Human Skin: A Review of Skin Modeling Approaches

The non-ionizing and non-invasive nature of THz radiation, combined with its high sensitivity to water, has made THz imaging and spectroscopy highly attractive for in vivo biomedical applications for many years. Among them, the skin is primarily investigated due to the short penetration depth of THz waves caused by the high attenuation by water in biological samples. However, a complete model of skin describing the THz-skin interaction is still needed. This is also fundamental to reveal the optical properties of the skin from the measured THz spectrum. It is crucial that the correct model is used, not just to ensure compatibility between different works, but more importantly to ensure the reliability of the data and conclusions. Therefore, in this review, we summarize the models applied to skin used in the THz regime, and we compare their adaptability, accuracy, and limitations. We show that most of the models attempt to extract the hydration profile inside the skin while there is also the anisotropic model that displays skin structural changes in the stratum corneum.

Breast glandularity and mean glandular dose assessment using a deep learning framework: Virtual patients study

PURPOSE

Breast dosimetry in mammography is an important aspect of radioprotection since women are exposed periodically to ionizing radiation due to breast cancer screening programs. Mean glandular dose (MGD) is the standard quantity employed for the establishment of dose reference levels in retrospective population studies. However, MGD calculations requires breast glandularity estimation. This work proposes a deep learning framework for volume glandular fraction (VGF) estimations based on mammography images, which in turn are converted to glandularity values for MGD calculations.

METHODS

208 virtual breast phantoms were generated and compressed computationally. The mammography images were obtained with Monte Carlo simulations (MC-GPU code) and a ray-tracing algorithm was employed for labeling the training data. The architectures of the neural networks are based on the XNet and multilayer perceptron, adapted for each task. The network predictions were compared with the ground truth using the coefficient of determination (r²).

RESULTS

The results have shown a good agreement for inner breast segmentation (r² = 0.999), breast volume prediction (r² = 0.982) and VGF prediction (r² = 0.935). Moreover, the DgN coefficients using the predicted VGF for the virtual population differ on average 1.3% from the ground truth values. Afterwards with the obtained DgN coefficients, the MGD values were estimated from exposure factors extracted from the DICOM header of a clinical cohort, with median(75 percentile) values of 1.91(2.45) mGy.

CONCLUSION

We successfully implemented a deep learning framework for VGF and MGD calculations for virtual breast phantoms.

Dosimetric effect of nanoparticles in the breast cancer treatment using INTRABEAM®system with spherical applicators in the presence of tissue heterogeneities: A Monte Carlo study

Using the 50 kV INTRABEAM^®IORT system after breast-conserving surgery: tumor recurrence and organs at risk (OARs), such as the lung and heart, long-term complications remain the challenging problems for breast cancer patients. So, the objective of this study was to address these two problems with the help of high atomic number nanoparticles (NPs). A Monte Carlo (MC) Simulation type EGSnrc C++ class library (egspp) with its Easy particle propagation (Epp) user code was used. The simulation was validated against the measured depth dose data found in our previous study (Tegaw,et al2020 Dosimetric characteristics of the INTRABEAM^®system with spherical applicators in the presence of air gaps and tissue heterogeneities,Radiat. Environ. Biophys. (10.1007/s00411-020-00835-0)) using the gamma index and passed 2%/2 mm acceptance criteria in the gamma analysis. Gold (Au) NPs were selected after comparing Dose Enhancement Ratios (DERs) of bismuth (Bi), Au, and platinum (Pt) NPs which were calculated from the simulated results. As a result, 0.02, 0.2, 2, 10, and 20 mg-Au/g-breast tissue were used throughout this study. These particles were not distributed in discrete but in a uniform concentration. For 20 mg-Au/g-breast tissue, the DERs were 3.6, 0.420, and 0.323 for breast tissue, lung, heart, respectively, using the 1.5 cm-diameter applicator (AP) and 3.61, 0.428, and 0.335 forbreast tissue, lung, and heart using the 5 cm-diameter applicator, respectively. DER increased with the decrease in the depth of tissues and increase in the effective atomic number (Z_eff) and concentration of Au NPs, however, there was no significant change as AP sizes increased. Therefore, Au NPs showed dual advantages such as dose enhancement within the tumor bed and reduction in the OARs (heart and lung).

Normalized glandular dose coefficients for digital breast tomosynthesis systems with a homogeneous breast model

This work aims at calculating and releasing tabulated values of dose conversion coefficients, DgN_DBT, for mean glandular dose (MGD) estimates in digital breast tomosynthesis (DBT). The DgN_DBT coefficients are proposed as unique conversion coefficients for MGD estimates, in place of dose conversion coefficients in mammography (DgN_DM or c, g, s triad as proposed in worldwide quality assurance protocols) used together with the T correction factor. DgN_DBT is the MGD per unit incident air kerma measured at the breast surface for a 0° projection and the entire tube load used for the scan. The dataset of polyenergetic DgN_DBT coefficients was derived via a Monte Carlo software based on the Geant4 toolkit. Dose coefficients were calculated for a grid of values of breast characteristics (breast thickness in the range 20-90 mm and glandular fraction by mass of 1%, 25%, 50%, 75%, 100%) and the simulated geometries, scan protocols, irradiation geometries and typical spectral qualities replicated those of six commercial DBT systems (GE SenoClaire, Hologic Selenia Dimensions, GE Senographe Pristina, Fujifilm Amulet Innovality, Siemens Mammomat Inspiration and IMS Giotto Class). For given breast characteristics, target/filter combination, tube voltage and half value layer (HVL), two spectra with two HVL values have been simulated in order to permit MGD estimates from experimental HVL values via mathematical interpolation from tabulated values. The adopted breast model assumes homogenous composition of glandular and adipose tissues; it includes a 1.45 mm thick skin envelope in place of the 4-5 mm envelope commonly adopted in dosimetry protocols. The simulation code was validated versus AAPM Task group 195 Monte Carlo reference data sets (absolute differences not higher than 1.1%) and by comparison to relative dosimetry measurements with radiochromic film in a PMMA test object (differences within the maximum experimental uncertainty of 11%). The calculated coefficients show maximum relative deviations of -17.6% and +6.1% from those provided by the DBT dose coefficients adopted in the EUREF protocol and of 1.5%, on average, from data in the AAPM TG223 report. A spreadsheet is provided for interpolating the tabulated DgN_DBT coefficients for arbitrary values of HVL, compressed breast thickness and glandular fraction, in the corresponding investigated ranges, for each DBT unit modeled in this work.

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.

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.

Is it important to define skin sub-volumes in breast brachytherapy?

Aim:

To evaluate clinically pertinent skin dose and volume parameters for the development of toxicities following accelerated partial breast irradiation (APBI).

Methods:

Three skin structures of various thicknesses inside the body (2 mm, 3 mm, 4 mm) were contoured over the treated breast retrospectively in a cohort of 62 women who underwent APBI using multi-catheter interstitial brachytherapy. The correlation statistics between the various skin structures and acute and late skin sequelae were evaluated using the Mann–Whitney U test and receiver-operating characteristic analysis. A p-value of <0·05 was considered significant.

Results:

At a median follow-up period of 54 months (range: 28–86), a significant correlation was seen between dose received by 0·2 (D0·2) cc of skin 4 mm inside the body as well as volume receiving 100% dose (V100) of skin 3 mm inside the body with cosmesis at 2 years and at last follow-up. The threshold for the two parameters for prediction of excellent or good cosmesis was 90% of the prescribed dose and 0·05 cc, respectively. No significant dosimetric or volumetric correlation was seen with other sequelae like wound dehiscence, fat necrosis, telangiectasia and atrophy.

Conclusion:

The results of this study support the use of dose and volumetric indices of the sub-volumes of the skin for correlation with clinical endpoints. However, the same should be validated prospectively in a larger cohort of women undergoing breast brachytherapy.

A reliable skin toxicity predictor in permanent breast seed implant brachytherapy

PURPOSE

To establish skin dose-outcome relationships using a reliable metric in permanent breast seed implant (PBSI).

METHODS

Sixty-seven consecutive patients who underwent PBSI at our institution were included. Skin doses were calculated using two skin dose indices: maximum point dose to the skin surface, D_max, and D_0.2cc for a 2-mm internal skin rind (a surrogate to the dose to 1 cm² area of skin) from CT-based postoperative treatment plans. Toxicity data were extracted from patients' charts and photographs. The associations between skin dose and skin toxicity were investigated using the analysis of variance, and the predictive performance of skin dose measures was evaluated using receiver operating characteristic curves.

RESULTS

For acute reactions, 49.3% of patients had Grade 1, 4.5% Grade 2, and 1.5% Grade 3 toxicity. For telangiectasia at 3 years, very minor and minimally apparent telangiectasia was observed in 25% of patients. Moderate but asymptomatic telangiectasia was observed in 9.1% of cases. Both metrics were significantly associated with the occurrence of acute toxicity and telangiectasia at 3 years (p < 0.01). The predictive values for D_max and D_0.2cc were 0.779 and 0.763, respectively, (p < 0.0001) for acute skin toxicity and 0.786 and 0.810 for telangiectasia (p < 0.0002). Extreme dose outliers (up to 878 Gy) and a high variability were observed for D_max but not for D_0.2cc, illustrating the superior reliability of D_0.2cc.

CONCLUSION

D_0.2cc, as an alternate skin dose measure to D_max, is a robust metric for measuring skin dose that is simple to calculate, yet is clinically relevant and not prone to inaccuracies inherent to point dose measurement.

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.

Monte Carlo study on optimal breast voxel resolution for dosimetry estimates in digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is currently used as an adjunct technique to digital mammography (DM) for breast cancer imaging. Being a quasi-3D image, DBT is capable of providing depth information on the internal breast glandular tissue distribution, which may be enough to obtain an accurate patient-specific radiation dose estimate. However, for this, information regarding the location of the glandular tissue, especially in the vertical direction (i.e. x-ray source to detector), is needed. Therefore, a dedicated reconstruction algorithm designed to localize the amount of glandular tissue, rather than for optimal diagnostic value, could be desirable. Such a reconstruction algorithm, or, alternatively, a reconstructed DBT image classification algorithm, could benefit from the use of larger voxels, rather than the small sizes typically used for the diagnostic task. In addition, the Monte Carlo (MC) based dose estimates would be accelerated by the representation of the breast tissue with fewer and larger voxels. Therefore, in this study we investigate the optimal DBT reconstructed voxel size that allows accurate dose evaluations (i.e. within 5%) using a validated Geant4-based MC code. For this, sixty patient-based breast models, previously acquired using dedicated breast computed tomography (BCT) images, were deformed to reproduce the breast during compression under a given DBT scenario. Two re-binning approaches were applied to the compressed phantoms, leading to isotropic and anisotropic voxels of different volumes. MC DBT simulations were performed reproducing the acquisition geometry of a SIEMENS Mammomat Inspiration system. Results show that isotropic cubic voxels of 2.73 mm size provide a dose estimate accurate to within 5% for 51/60 patients, while a comparable accuracy is obtained with anisotropic voxels of dimension 5.46  ×  5.46  ×  2.73 mm³. In addition, the MC simulation time is reduced by more than half in respect to the original voxel dimension of 0.273  ×  0.273  ×  0.273 mm³ when either of the proposed re-binning approaches is used. No significant differences in the effect of binning on the dose estimates are observed (Wilcoxon-Mann-Whitney test, p-value  >  0.4) between the 0° the 23° (i.e. the widest angular range) exposure.

An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images

PURPOSE

To develop and evaluate a new automatic classification algorithm to identify voxels containing skin, vasculature, adipose, and fibroglandular tissue in dedicated breast CT images.

METHODS

The proposed algorithm combines intensity- and region-based segmentation methods with energy minimizing splines and unsupervised data mining approaches for classifying and segmenting the different tissue types. Breast skin segmentation is achieved by a region-growing method which uses constraints from the previously extracted skin centerline to add robustness to the model and to reduce the false positive rate. An energy minimizing active contour model is then used to classify adipose tissue voxels by including gradient flow and region-based features. Finally, blood vessels are separated from fibroglandular tissue by a k-means clustering algorithm based on automatically extracted shape-based features. To evaluate the accuracy of the algorithm, two sets of 15 different patient breast CT scans, each acquired with different breast CT systems and acquisition settings were obtained. Three slices from each scan were manually segmented under the supervision of an experienced breast radiologist and considered the gold standard. Comparisons with manual segmentation were quantified using five similarity metrics: Dice similarity coefficient (DSC), sensitivity, conformity coefficient, and two Hausdorff distance measures. To evaluate the robustness to image noise, the segmentation was repeated after separately adding Gaussian noise with increasing standard deviation (in four steps, from 0.01 to 0.04) to an additional 15 slices from the first dataset. In addition, to evaluate vasculature classification, three different pre- and postcontrast injection patient breast CT images were classified and compared. Finally, DSC was also used for quantitative comparisons with previously proposed approaches for breast CT tissue classification using 10 images from the first dataset.

RESULTS

The algorithm showed a high accuracy in classifying the different tissue types for both breast CT systems, with an average DSC of 95% and 90% for the first and second image dataset, respectively. Furthermore, it demonstrated to be robust to image noise with a robustness to image noise of 85%, 83%, 79%, and 71% for the images corrupted with the four increasing noise levels. Previous methods for breast tissues classification resulted, for the tested dataset, in an average global DSC of 87%, while our approach resulted in a global average DSC of 94.5%.

CONCLUSIONS

The proposed algorithm resulted in accurate and robust breast tissue classification, with no prior training or threshold setting. Potential applications include breast density quantification and tissue pattern characterization (both biomarkers of cancer development), simulation-based radiation dose analysis, and patient data-based phantom design, which could be used for further breast imaging research.

Average glandular dose coefficients for pendant-geometry breast CT using realistic breast phantoms

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper's ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51  ±  0.06 and 0.54  ±  0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72  ±  0.01, 2.75  ±  0.01) and (2.77  ±  0.03, 2.82  ±  0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10  ±  0.17, 3.21  ±  0.11) and (3.01  ±  0.32, 3.19  ±  0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30 mm  ×  30 mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers.

Towards standardization of x-ray beam filters in digital mammography and digital breast tomosynthesis: Monte Carlo simulations and analytical modelling

In digital breast tomosynthesis and digital mammography, the x-ray beam filter material and thickness vary between systems. Replacing K-edge filters with Al was investigated with the intent to reduce exposure duration and to simplify system design. Tungsten target x-ray spectra were simulated with K-edge filters (50 µm Rh; 50 µm Ag) and Al filters of varying thickness. Monte Carlo simulations were conducted to quantify the x-ray scatter from various filters alone, scatter-to-primary ratio (SPR) with compressed breasts, and to determine the radiation dose to the breast. These data were used to analytically compute the signal-difference-to-noise ratio (SDNR) at unit (1 mGy) mean glandular dose (MGD) for W/Rh and W/Ag spectra. At SDNR matched between K-edge and Al filtered spectra, the reductions in exposure duration and MGD were quantified for three strategies: (i) fixed Al thickness and matched tube potential in kilovolts (kV); (ii) fixed Al thickness and varying the kV to match the half-value layer (HVL) between Al and K-edge filtered spectra; and, (iii) matched kV and varying the Al thickness to match the HVL between Al and K-edge filtered spectra. Monte Carlo simulations indicate that the SPR with and without the breast were not different between Al and K-edge filters. Modelling for fixed Al thickness (700 µm) and kV matched to K-edge filtered spectra, identical SDNR was achieved with 37-57% reduction in exposure duration and with 2-20% reduction in MGD, depending on breast thickness. Modelling for fixed Al thickness (700 µm) and HVL matched by increasing the kV over (0,4) range, identical SDNR was achieved with 62-65% decrease in exposure duration and with 2-24% reduction in MGD, depending on breast thickness. For kV and HVL matched to K-edge filtered spectra by varying Al filter thickness over (700, 880) µm range, identical SDNR was achieved with 23-56% reduction in exposure duration and 2-20% reduction in MGD, depending on breast thickness. These simulations indicate that increased fluence with Al filter of fixed or variable thickness substantially decreases exposure duration while providing for similar image quality with moderate reduction in MGD.