Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Facultad de Ciencias, Instituto de Física, Universidad de la República, Montevideo, Uruguay.
Med Phys. 2022 Aug;49(8):5423-5438. doi: 10.1002/mp.15785. Epub 2022 Jun 8.
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.
To develop and validate a method to generate patient-derived, heterogeneous digital breast phantoms for breast dosimetry in mammography and DBT.
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 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.
The average D N estimated for the proposed phantoms was concordant with that absorbed by the patient-specific phantoms to within 5% (CC) and 4% (MLO). These D N estimates were over 30% lower than those estimated with the homogeneous models, which overestimated the average D N by 43% (CC), and 32% (MLO) compared to the patient-specific phantoms.
The developed phantoms can be used for dosimetry simulations to improve the accuracy of dose estimates in mammography and DBT.
了解乳房纤维腺体组织在乳房 X 线摄影和数字乳腺断层合成（DBT）中吸收的辐射剂量的幅度和可变性对于评估风险与收益至关重要。尽管几十年来一直提出并使用均匀乳房模型来达到这一目的，但它们并不能准确反映乳房中纤维腺体组织的实际不均匀分布，导致这些方式的剂量估计存在偏差。
开发并验证一种用于乳房 X 线摄影和 DBT 中乳房剂量学的基于患者的、异质数字乳腺体模的方法。
所提出的体模是从为多个厚度生成的基于患者的压缩乳房模型开始开发的，这些模型代表了在乳房 X 线摄影和 DBT 中获得的两种标准视图，即头尾（CC）和内外斜（MLO）。内部，乳房体模被定义为由脂肪/纤维腺体组织混合物组成，具有非空间均匀的相对浓度。这些实质分布是从基于患者乳房计算机断层扫描数据的先前描述的模型中获得的，这些数据经历了模拟压缩。根据这些分布，可以为任何腺体分数（1%-100%）和乳房厚度（12-125 毫米）生成两种视图的体模。使用涉及乳房中纤维腺体组织实际患者分布的 88 个患者特异性体模，对体模进行验证，以评估其在患者乳房样本中平均归一化腺体剂量（D N）估计的准确性，并与使用类似于目前用于乳房剂量学的均匀模型获得的结果进行比较。
对于提出的体模，估计的平均 D N 与患者特异性体模吸收的 D N 之间的差异在 5%（CC）和 4%（MLO）以内。与使用均匀模型相比，这些 D N 估计值低 30%以上，均匀模型高估了平均 D N，与患者特异性体模相比，CC 为 43%，MLO 为 32%。
所开发的体模可用于剂量模拟，以提高乳房 X 线摄影和 DBT 中剂量估计的准确性。
