TY - JOUR
T1 - Patient-derived heterogeneous breast phantoms for advanced dosimetry in mammography and tomosynthesis
AU - Caballo, Marco
AU - Rabin, Carolina
AU - Fedon, Christian
AU - Rodríguez-Ruiz, Alejandro
AU - Diaz, Oliver
AU - Boone, John M.
AU - Dance, David R.
AU - Sechopoulos, Ioannis
N1 - Funding Information:
The authors would like to thank Dr. Paul Segars for his support in visualization and rendering of the compressed breast shapes used in this study. This research was supported in part by Grant R01CA181171 from the National Cancer Institute, National Institutes of Health, and Grant IIR13262248 from the Susan G. Komen Foundation for the Cure. The authors would like to thank the Comisión Sectorial de Investigación Científica (CSIC) under project C681 in Uruguay. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, the National Institutes of Health, the Komen Foundation, or the Comisión Sectorial de Investigación Científica.
Funding Information:
The authors would like to thank Dr. Paul Segars for his support in visualization and rendering of the compressed breast shapes used in this study. This research was supported in part by Grant R01CA181171 from the National Cancer Institute, National Institutes of Health, and Grant IIR13262248 from the Susan G. Komen Foundation for the Cure. The authors would like to thank the Comisión Sectorial de Investigación Científica (CSIC) under project C681 in Uruguay. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, the National Institutes of Health, the Komen Foundation, or the Comisión Sectorial de Investigación Científica.
Publisher Copyright:
© 2022 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.
PY - 2022/8
Y1 - 2022/8
N2 - 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 (DgN) 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 DgN estimated for the proposed phantoms was concordant with that absorbed by the patient-specific phantoms to within 5% (CC) and 4% (MLO). These DgN estimates were over 30% lower than those estimated with the homogeneous models, which overestimated the average DgN 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.
AB - 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 (DgN) 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 DgN estimated for the proposed phantoms was concordant with that absorbed by the patient-specific phantoms to within 5% (CC) and 4% (MLO). These DgN estimates were over 30% lower than those estimated with the homogeneous models, which overestimated the average DgN 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.
KW - Breast density
KW - Breast dosimetry
KW - Digital breast tomosynthesis
KW - Digital phantoms
KW - Mammography
KW - UT-Hybrid-D
UR - https://www.scopus.com/pages/publications/85131373353
U2 - 10.1002/mp.15785
DO - 10.1002/mp.15785
M3 - Article
AN - SCOPUS:85131373353
SN - 0094-2405
VL - 49
SP - 5423
EP - 5438
JO - Medical physics
JF - Medical physics
IS - 8
ER -