Division of Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Biometrics. 2023 Dec;79(4):3728-3738. doi: 10.1111/biom.13847. Epub 2023 Mar 13.
Mammography is the primary breast cancer screening strategy. Recent methods have been developed using the mammogram image to improve breast cancer risk prediction. However, it is unclear on the extent to which the effect of risk factors on breast cancer risk is mediated through tissue features summarized in mammogram images and the extent to which it is through other pathways. While mediation analysis has been conducted using mammographic density (a summary measure within the image), the mammogram image is not necessarily well described by a single summary measure and, in addition, such a measure provides no spatial information about the relationship between the exposure risk factor and the risk of breast cancer. Thus, to better understand the role of the mammogram images that provide spatial information about the state of the breast tissue that is causally predictive of the future occurrence of breast cancer, we propose a novel method of causal mediation analysis using mammogram image mediator while accommodating the irregular shape of the breast. We apply the proposed method to data from the Joanne Knight Breast Health Cohort and leverage new insights on the decomposition of the total association between risk factor and breast cancer risk that was mediated by the texture of the underlying breast tissue summarized in the mammogram image.
乳腺 X 线摄影是乳腺癌筛查的主要策略。最近已经开发出了一些使用乳腺 X 线照片来改善乳腺癌风险预测的方法。然而，尚不清楚危险因素对乳腺癌风险的影响在多大程度上是通过乳腺 X 线照片中总结的组织特征来介导的，以及在多大程度上是通过其他途径来介导的。虽然已经使用乳腺密度（图像中的一种总结性测量指标）进行了中介分析，但乳腺 X 线照片不一定可以通过单一的总结性测量指标来很好地描述，而且这种测量指标也没有提供关于暴露风险因素与乳腺癌风险之间关系的空间信息。因此，为了更好地了解提供关于乳腺组织状态的空间信息的乳腺 X 线照片的作用，这些信息对未来发生乳腺癌具有因果预测性，我们提出了一种使用乳腺 X 线照片中介的新的因果中介分析方法，同时适应了乳房的不规则形状。我们将所提出的方法应用于乔安妮·奈特乳腺健康队列的数据，并利用在乳腺 X 线照片中总结的基础乳腺组织纹理介导的风险因素与乳腺癌风险之间的总关联的分解方面的新见解。
