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

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.

Characterization of a new radiochromic film (LD-V1) using mammographic beam qualities

PURPOSE

Radiochromic film (RCF) is a detector that can obtain a two-dimensional dose distribution with high resolution; it is widely used in medical and industrial fields. Several types of RCFs exist based on their application. The type of RCF mainly used for mammography dose assessment has been discontinued; however, a new type of RCF (LD-V1) has been distributed as a successor. Since the medical use of LD-V1 has rarely been studied, we investigated the response characteristics of LD-V1 in mammography.

METHODS

Measurements were performed using Mo/Mo and Rh/Ag on a Senographe Pristina mammography device (GE, Fairfield, CT, USA). The reference air kerma was measured using a parallel-plate ionization chamber (PPIC) (C-MA, Applied Engineering Inc, Tokyo, Japan). Pieces of LD-V1 film model were irradiated at the same position where the reference air kerma in air was measured by the PPIC. Irradiation was performed using the time scale method based on the load on the equipment. Two methods of irradiation were considered: placing the detector in air and on the phantom. The LD-V1 was scanned five times at 72 dpi in RGB (48 bit) mode using a flatbed scanner (ES-G11000, Seiko Epson Corp, Nagano, Japan) 24 h following irradiation. The response ratio of the reference air kerma and the air kerma obtained from the LD-V1 were compared and examined for each beam quality and air kerma range.

RESULTS AND DISCUSSION

When the beam quality was altered, the response ratio varied from 0.8 to 1.2 with respect to the measurement value of the PPIC; however, some outliers were observed. Response ratios were highly variable in the low-dose range; however, as the air kerma increased, the ratios approached 1. Thus, LD-V1 does not need calibration for each beam quality used in mammography. LD-V1 enables air kerma evaluation by creating air kerma response curves under certain X-ray conditions used in mammography.

CONCLUSION

We suggest that the dose range be limited to 12 mGy or more to keep the response variation with beam qualities below ±20%. If further measurement is required for reducing the response variation, the dose range should be shifted to a higher dose range.

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.

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.

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

BACKGROUND

Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing.

AIMS

To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.

MATERIALS AND METHODS

G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes.

RESULTS

This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

DISCUSSION

Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics.

CONCLUSION

The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

Towards 4D dedicated breast CT perfusion imaging of cancer: development and validation of computer simulated images

Dedicated breast CT is a fully tomographic breast imaging modality with potential for various applications throughout breast cancer care. If implemented to perform dynamic contrast-enhanced (CE) imaging (4D breast CT), it could be useful to obtain functional information at high combined spatio-temporal resolution. Before developing a 4D dedicated breast CT system, a computer simulation method for breast CT perfusion imaging is proposed. The simulation uses previously developed patient-based 4D digital breast phantoms, and generates realistic images with the selected acquisition parameters, allowing to investigate the effect of different acquisition settings on image quality. The simulation pipeline includes all steps of the image generation process, from ray tracing and scatter map generation, to the addition of realistic resolution losses and noise models. The pipeline was validated against experimental measurements performed on physical phantoms with a dedicated breast CT system, in terms of average error compared to ground truth projections (6.0%  ±  1.65%), Hounsfield unit (HU) values in a homogeneous phantom (acquired: -149 HU  ±  2 HU; simulated:  -140 HU  ±  2 HU), signal-to-noise ratio (SNR) (average error 6.7%  ±  4.2%), noise power spectra (NPS) (average error 4.3%  ±  2.5%), modulation transfer function (MTF) (average error 8.4%  ±  7.2%), and attenuation of different adipose/glandular equivalent mixtures (average error 6.9%  ±  4.0%) and glandular plus iodinated contrast medium concentrations equivalent mixtures (average error of 9.1%  ±  9.0%). 4D patient images were then simulated for different 4D digital breast phantoms at different air kerma levels to determine the effect of noise on the extracted tumor perfusion curves. In conclusion, the proposed pipeline could simulate images with a good level of realism, resulting in a tool that can be used for the design, development, and optimization of a 4D dedicated breast CT system.

Dose profile evaluation in digital breast tomosynthesis exposition using radiochromic film

Digital Breast Tomosynthesis (DBT) is an efficient method to diagnose changes in the breast tissues. However, it may promote some future detriment to the patient exposed in this test. The future effects can be evaluating using absorbed dose values. A mammographic phantom should be chosen to simulate approximately the properties of a compressed breast in terms of the primary and dispersed radiation spectrum that exits its lower surface. The use of PMMA has important advantages. It is cheaper than substitutes for specially manufactured fabrics and is more available. The objective of this work will be to estimate the dose profile that a real breast would receive during a DTB examination. For this purpose a breast phantom with acrylic materials (PMMA) and dimensions similar to those of a real breast will be constructed, and the dose will be measured on the surface (ESAK profile) and in the middle cut (air kerma profile) of the breast phantom using the radiochromic film.

Geant4 physics list comparison for the simulation of phase-contrast mammography (XPulse project)

PURPOSE

Breast cancer is the most frequent cancer in women. Early and accurate detection of the disease is a major factor in patient survival. To this end, phase-contrast imaging has gained significant interest in recent years. The aim of this work was to validate the physics models of a Geant4 mammography imaging simulation (in the context of the XPulse project) by comparing to EGSnrc results.

METHODS

We used three Geant4 electromagnetic physics lists of the version 10.4 of the toolkit: Standard, Livermore and Penelope. We calculated energy distributions in homogeneous and inhomogeneous phantoms and breast doses in DICOM images. The simulations used photon beams of energies 20-100 keV. The Geant4 calculations were compared with EGSnrc/DOSXYZnrc simulations.

RESULTS

We found a very good agreement between the Standard Electromagnetic option 4 and Livermore Physics Lists (within 1% for all beam energies). Larger differences were found between Standard Electromagnetic option 4 and Penelope Physics Lists (about 4%). The agreement of longitudinal energy distributions between Geant4 Standard Electromagnetic option 4 and EGSnrc was good in water and light biological materials, but important discrepancies were found in heavy elements. We confirmed with both codes that dose to the breast is minimal at beam energy around 60 keV.

CONCLUSIONS

Overall, we found good agreement between the option 4 of the Standard Electromagnetic physics list and Livermore physics lists of Geant4, as well as EGSnrc for materials relevant to mammography screening. Further investigations are needed for the case of heavier materials.

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.