Improving Perception in Digital Breast Tomography

项目摘要 乳腺癌筛查是世界各地妇女常规医疗保健的重要组成部分。这个 现代标准筛查方法是全场数字乳房摄影(FFDM)，其中两种检查方法-- 创建整个乳房厚度的三维数字X光图像。数字乳房 断层合成(DBT)是一项重要的进步，它创建由一组 通过乳房的X射线切片。DBT已被证明可以提高准确度--无论是灵敏度还是 乳腺癌筛查的特异性--仅通过FFDM，但临床应用相对较少 速度慢，部分原因是使用DBT的考试比单独使用FFDM需要的时间要长得多。这个 建议的研究将使用医学图像感知实验来改进DBT的搜索策略 图像，目的是提高乳腺癌筛查的速度和准确性。确实有 三个目标。目标1：研究眼球运动模式及其与错误的关系 放射科医生读取DBT图像以确定哪种搜索策略明显更快 和/或比其他人更准确。眼球运动将被测量，而三组 放射科医生阅读DBT：DBT培训前的放射科医生，DBT培训后的放射科医生，以及DBT专家。 这些数据将揭示由专家传授的策略是否与使用的策略相同 由实践中的专家，以及受训者在培训后是否按照专家的建议行事。目标2： 通常，放射科医生会使用FFDM图像来指导后续的DBT图像搜索。在……里面 目标2，这将颠倒过来。假设一部DBT“电影”的初始预览会有所改进 通过引导读者到Ffdm中的重要基因座来实现乳腺癌筛查的速度和/或准确性 并协助进一步检查DBT图像。目标3：与FFDM相比，DBT大大 增加可供搜索的图像数量。这将是一个非常好的时机 费力且不需要仔细检查每个切片的每一个像素。一个读者要在多少个地区阅读 需要专注于，以便合理地确定一些癌症的迹象，如果存在，将吸引 注意了吗？要回答这个问题，我们需要知道距离注视有多远 癌症的迹象是可以检测到的。专家观察员和非专家观察员的研究将结合起来 使我们能够测量这些距离。结合来自AIM 1的眼球跟踪数据，这些数据 可用于确定是否可以通过培训放射科医生使用特定搜索来降低错误率 模式。这项研究计划将产生低成本的干预措施，以改善DBT的使用 从而提高乳腺癌筛查的救命功效。

Project Summary Breast cancer screening is an important part of routine medical care for women around the world. The modern standard screening method is Full Field Digital Mammography (FFDM) in which two- dimensional, digital x-ray images are created of the entire thickness of the breast. Digital Breast Tomosynthesis (DBT) is an important advance that creates a 3D volume of images, consisting of a set of x-ray slices through the breast. DBT has been shown to improve accuracy - both the sensitivity and specificity - of breast cancer screening over FFDM alone, but clinical adoption has been relatively slow, in part because exams with DBT take significantly longer to interpret than do FFDM alone. The proposed studies will use medical image perception experiments to improve search strategies for DBT images, with the goal of increasing the speed and accuracy of breast cancer screening. There are three aims. Aim 1: To examine the pattern of eye movements and their relationship to errors when radiologists read DBT images in order to determine which search strategies are significantly faster and/or more accurate than others. Eye movements will be measured while three groups of radiologists read DBT: radiologists prior to DBT training, just after DBT training, and DBT experts. These data will reveal whether the strategies, taught by experts, are the same as the strategies used by experts in practice and whether, after training, trainees do what the experts recommend. Aim 2: Typically, a radiologist would use the FFDM image to guide subsequent search of DBT images. In Aim 2, this will be reversed. The hypothesis is that an initial preview of a DBT “movie” will improve speed and/or accuracy of breast cancer screening by guiding the reader to important loci in the FFDM image and by aiding further examination of the DBT images. Aim 3: Compared to FFDM, DBT greatly increases the number of images that are available to be searched. It would be extremely time consuming and unnecessary to scrutinize every pixel of every slice. How many regions does a reader need to fixate upon in order to be reasonably sure that some sign of cancer, if present, will attract attention? To answer this question, we need to know the distance away from fixation at which different signs of cancer can be detected. A combination of studies with expert and non-expert observers will enable us to measure these distances. Combined with the eye tracking data from Aim 1, these data can be used to determine if error rates can be reduced by training radiologists to use specific search patterns. This program of research will yield low-cost interventions that can improve the use of DBT and, thus, enhance the life-saving effectiveness of breast cancer screening