Effect of Breast Density on Screening Recall with Digital Breast Tomosynthesis

描述（由申请人提供）：目前，美国乳房x光筛查的回呼率很高，约为10%。由于组织重叠对二维投影图像的影响，许多妇女，特别是乳房致密的妇女，被召回进行“假病变”的额外成像，基本上是可疑的正常组织重叠，经过诊断检查，证明是正常的。数字乳房断层合成（DBT）是一种新的三维x射线成像方式，它通过多个低剂量源投影重建乳房断层图像。在DBT中，组织叠加的影响在很大程度上从图像集中消除了，因此与乳房x光检查相比，提供了更好的乳房组织可视化。早期临床试验表明，当DBT纳入筛查设置时，假阳性回忆最多可减少40%。然而，当DBT纳入筛查范式时，辐射剂量更高。因此，必须仔细权衡DBT的潜在益处与可能增加的剂量。确定从DBT成像中获益最多的女性子集是至关重要的。为了解决这一问题，我们的研究将比较乳腺密度和总体乳腺实质复杂性对数字乳房x线摄影（DM）和DBT乳腺癌筛查中召回决策的影响。我们的假设是，复杂的实质模式（即致密和/或质地复杂的乳房）在DM的假阳性发现中被召回的可能性比在筛查过程中纳入DBT时更高。为此，我们建议发展一种影像学指标来表征乳腺实质组织的复杂性。目前，还没有一个能全面反映实质复杂性的标准词汇。乳腺密度是标准乳腺摄影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与先进的图像纹理特征结合起来，形成一个定量的乳房复杂性指数（BCI），该指数可用于识别从DBT筛查中获益最多的女性子集。快速发展的技术和潜在的卓越性能将决定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，用于筛查致密和/或结构复杂的乳房，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.