Improving Perception in Digital Breast Tomography

改善数字乳腺断层扫描的感知

基本信息

批准号：
9751254
负责人：
Jeremy M Wolfe
金额：
$ 43.98万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-06 至 2021-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9751254
关键词：
3-Dimensional Address Adoption Attention Basic Science Breast Breast Cancer Detection Caring Classification Classification Scheme Clinical Complex Consumption Data Detection Development Diagnostic radiologic examination Digital Breast Tomosynthesis Digital Mammography Digital X-Ray Discrimination Effectiveness Exposure to Eye Eye Movements Goals Growth Image Imagery Knowledge Learning Lesion Life Malignant Neoplasms Mammography Measures Medical Medical Imaging Methods Modality Modernization Nature Pathologic Pattern Perception Performance Process Radiology Specialty Reader Reading Recommendation Research Roentgen Rays Savings Sensitivity and Specificity Shapes Slice Speed Testing Thick Time Training Woman base chest computed tomography clinical practice comparative digital evidence base experience experimental study imaging modality impression improved insight intervention cost malignant breast neoplasm movie programs radiologist sample fixation screening tomography tomosynthesis tool two-dimensional visual process visual search

项目摘要

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

项目概要乳腺癌筛查是世界各地女性常规医疗护理的重要组成部分。现代标准筛查方法是全视野数字乳腺 X 线摄影 (FFDM)，其中两种 - 创建乳房整个厚度的三维数字 X 射线图像。断层合成 (DBT) 是一项重要的进步，可创建 3D 图像体，由一组图像组成通过乳房的 X 射线切片已被证明可以提高准确性 - 灵敏度和灵敏度。特异性 - 乳腺癌筛查优于单独的 FFDM，但临床采用相对较少速度很慢，部分原因是使用 DBT 进行的考试的解读时间比单独使用 FFDM 的时间要长得多。拟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，旨在提高乳腺癌筛查的速度和准确性。三个目标 1：检查眼球运动的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/或比其他组更准确地测量眼球运动。放射科医生阅读 DBT：放射科医生接受 DBT 培训之前、刚刚接受 DBT 培训以及 DBT 专家。这些数据将揭示专家教授的策略是否与实际使用的策略相同目标 2：通常，放射科医生会使用 FFDM 图像来指导后续 DBT 图像的搜索。目标 2，这将被逆转，假设 DBT“电影”的初始预览将会改进。通过引导读者找到 FFDM 中的重要位点来提高乳腺癌筛查的速度和/或准确性目标 3：与 FFDM 相比，DBT 显着提高。增加可搜索的图像数量将非常耗时。读者需要花费多少个区域来仔细检查每个切片的每个像素。需要注意，以便合理地确定某些癌症迹象（如果存在）会吸引要回答这个问题，我们需要知道注视点的距离有哪些不同？专家和非专家观察员的联合研究将可以检测到癌症的迹象。结合目标 1 的眼动追踪数据，我们能够测量这些距离。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该研究计划将产生可以改善 DBT 使用的低成本干预措施。从而提高乳腺癌筛查的挽救生命效果