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.

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

Quantitative breast elastography from B-mode images.

PURPOSE: Elastography images provide information about the mechanical properties of soft tissue in a noninvasive way and can be useful to identify abnormalities and ascertain differential diagnoses of suspicious prior findings obtained through mammography ultrasound. In this work we investigate, from a physics point of view, the feasibility of quantifying the Young's modulus of breast tissue from the autocorrelation of a diffuse acoustic field computed from a sequence of B-mode images acquired through conventional ultrasound scanners. METHODS: Inspired in the seismological approach of retrieving the Green's function by cross-correlation of diffuse fields, we obtained a quantitative expression that relates the local shear modulus of soft tissue to the autocorrelation of the displacement field generated by the presence of an acoustic diffuse field in the medium. In addition, we designed a mechanical prototype device adaptable to the breast anatomy, in order to create the necessary conditions in terms of diffuse field generation. The device is easy to handle, and its positioning does not interfere with the ultrasonic probe, being friendly to use within the clinical environment. The displacement field was measured from a sequence of B-mode images acquired at standard frame rates (30-50 Hz) with conventional ultrasound equipment. This method was tested in a breast tissue mimicking phantom using two standard ultrasound scanners (Toshiba Nemio NX and SIUI (Shantou Institute of Ultrasonic Instruments) Apogee 3800) and an open source research device (Verasonics V3.07 US). We also performed an in vivo measurement as a preliminary validation. RESULTS: In the reconstructed Young's modulus maps the inclusions were identified and the obtained quantitative results for an inclusion and the background of the phantom were 60.0 ± 4.0 and 20.4 ± 0.5 KPa for the Toshiba equipment, 65.5 ± 6.9 and 22.6 ± 2.7 KPa for the SIUI equipment and 67.2 ± 7.3 KPa and 22.6 ± 2.8 KPa for the Verasonic scanner. These results are in good agreement with the values reported by the phantom's manufacturer of 60 and 20 KPa for the inclusion and the background, respectively. In the case of the in vivo measurement, the obtained images are in accordance with the patient known pathology (BI-RADS 5, Infiltrating Ductal Carcinoma, Score 6). The pathological breast showed a heterogeneous elasticity map with a mean Young's modulus of 98.1 ± 12.9 KPa, while the normal breast displayed a homogeneous map with a mean Young's modulus of 24.7 ± 8.1 KPa. CONCLUSIONS: We successfully reconstructed the Young's modulus map of the breast tissue mimicking phantom and of a real breast tumor using B-mode images acquired with conventional ultrasound scanners. The results obtained in this work support that our technique can be developed as a medical tool to obtain quantitative breast tissue elasticity maps.

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.