Effect of Breast Density on Screening Recall with Digital Breast Tomosynthesis

描述(申请人提供)：目前，美国筛查乳房X光检查的回复率很高，约为10%。由于2D投影图像上的组织叠加的影响，许多女性，特别是乳房致密的女性，会被召回进行额外的“假病变”成像，即本质上看起来可疑的正常组织叠加，经过诊断检查后证明是正常的。数字乳腺断层合成(DBT)是一种新的三维X射线成像方式，它由多个低剂量源投影重建乳腺断层图像。在DBT中，组织叠加的影响在很大程度上从图像集中去除，从而提供了比乳房X光摄影更好的乳房组织可视化。早期临床试验表明，当DBT被纳入筛查设置时，假阳性召回最高可减少40%。然而，当DBT被纳入筛查范例时，存在更高的辐射剂量。因此，必须仔细权衡DBT的这一潜在益处与潜在剂量的增加。确定将从DBT成像中受益最多的一组妇女是至关重要的。为了解决这一问题，我们的研究将比较乳房密度和总体乳房实质复杂性对数字乳房X光摄影(DM)和DBT乳腺癌筛查中召回决策的影响。我们的假设是，与将DBT纳入筛查过程中相比，复杂的实质模式(即致密和/或结构复杂的乳房)在DM患者中因假阳性发现而被召回的可能性更高。为此，我们建议开发一种用于表征乳腺实质组织复杂性的成像指数。目前，还没有一个标准的词汇来全面反映实体的复杂性。乳房密度是标准乳房X光摄影BIRADS词典中唯一基于图像的描述符。因此，我们建议将标准密度测量和高级图像纹理特征结合成一个定量的乳房复杂性指数(BCI)，该指数可以用来识别将从DBT筛查中受益最大的女性子集。快速发展的技术和卓越性能的潜力将决定DBT在临床实践中的作用。如果我们的假设被证明是正确的，DBT可以取代或补充DM，用于筛查乳房致密和/或结构复杂的女性，以减少不必要的召回和额外的诊断成像程序。

DESCRIPTION (provided by applicant): Currently, call-back rates for screening mammography in the U.S. are high at about 10%. Due to the effect of tissue superimposition on the 2D projection images, many women, especially women with dense breasts, are recalled for additional imaging of "pseudo-lesions", essentially suspicious-looking superimpositions of normal tissues which, after diagnostic workup, prove to be normal. Digital breast tomosynthesis (DBT) is a new 3D x-ray imaging modality in which tomographic breast images are reconstructed from multiple low-dose source projections. In DBT, the effects of tissue superposition are largely removed from the image set, thereby providing superior breast tissue visualization compared to mammography. Early clinical trials suggest up to a 40% reduction in false positive recalls when DBT is incorporated in the screening setting. There is however, a higher radiation dose when DBT is incorporated into the screening paradigm. Therefore this potential benefit of DBT must be carefully weighed against a potential increase of dose. The identification of a subset of women who would benefit most from DBT imaging is critical. To address this concern, our study will compare the effect of breast density and overall breast parenchymal complexity on the recall decision in breast cancer screening with digital mammography (DM) versus DBT. Our hypothesis is that complex parenchymal patterns (i.e., dense and/or texturally complex breasts) have a higher likelihood of being recalled for false positive findings with DM than when DBT is incorporated in the screening process. Towards this end, we propose to develop an imaging index for characterizing breast parenchymal tissue complexity. Currently, there is no standard lexicon to comprehensively reflect parenchymal complexity. Breast density is the only such image-based descriptor in the standard mammography BIRADS lexicon. Therefore, we propose to combine the standard density measures with advanced image texture features into a quantitative breast complexity index (BCI) that can be used to identify a subset of women who would benefit most from DBT screening. The rapidly evolving technology and the potential for superior performance will determine the role of DBT in clinical practice. If our hypothesis proves to be true, DBT could replace or complement DM for the screening of women with dense and/or texturally complex breasts, to reduce unnecessary recalls and additional diagnostic imaging procedures.