Improvement of microcalcification detection in digital breast tomosynthesis

描述(申请人提供)：筛查乳房X光检查的灵敏度和特异度有限。数字乳腺断层扫描(DBT)是一种新兴的检查方法，已被证明可以显著提高软组织病变的检测和定性。然而，初步研究表明，微小的微钙化(MC)簇通常是早期乳腺癌的唯一迹象，在DBT中很难观察到。一些人建议在筛查中同时使用DBT和FFDM(即在两个视点的FFDM中增加一个或两个视点的DBT，以便FFDM可用于MC检测，而DBT可用于质量检测)。这种方法会增加成像成本、阅读时间和患者剂量，这些都是将DBT引入临床实践的主要考虑因素。密歇根大学计算机辅助诊断研究实验室(UM)和GE Global Research(GE)之间拟议的合作伙伴关系的主要目标是开发一种综合实用的方法，在不增加患者剂量的情况下解决DBT中的MC可视化和检测问题，从而促进最终由DBT取代FFDM。为了实现这一目标，我们提出了两个具体目标：(SA1)开发专门设计的MC增强方法，以改善DBT中MC的人和机器可视化，并开发计算机辅助检测(CAD)系统，以突出重要的MC簇；(SA2)在DBT工作站上实现所开发的MC增强和CAD读取工具，并进行观察者性能研究，以比较DBT中的MC检测和FFDM中的MC检测。将执行以下任务以完成特定目标：(1)执行模体研究以确定用于数据收集的最佳图像采集参数组，(2)收集用于开发算法和观察者研究的人类受试者DBT的数据库，(3)开发病变特定重建和MC增强方法以提高DBT中MC的可见性，以供放射科医生阅读和计算机检测，(4)开发计算机视觉方法来检测MC候选对象，(5)开发MC分析方法以减少假阳性(FP)和不显著的CAD标记，(6)设计两视图分析以进一步减少FP，(7)研究MC的检测对重建方法和CT合成采集参数的依赖关系，以及(8)设计一个基于MC增强和CAD辅助工具的DBT工作站，突出显示重要的MC，供放射科医生阅读。我们推测，专门设计的DBT显示系统可以帮助放射科医生检测DBT中的MC，其准确度至少与FFDM相当。为了验证这一假设，我们将(9)进行观察者ROC研究，以比较在三种情况下MC的检测准确性：(A)不带CAD的双视图DBT与不带CAD的双视FFDM，(B)带CAD的双视图DBT与带CAD的双视FFDM，以及(C)具有CAD的CC-view FFDM加MLO-view DBT与带CAD的双视FFDM的特殊协议。

DESCRIPTION (provided by applicant): Screening mammography has limited sensitivity and specificity. Digital Breast Tomosynthesis (DBT) is an emerging modality that has been shown to significantly improve the detection and characterization of soft- tissue lesions. However, initial studies have shown that subtle microcalcification (MC) clusters, which are often the only sign of early breast cancer, can be difficult to visualize in DBT. Some have suggested that DBT be used in parallel with FFDM in screening, (i.e., adding one- or two-view DBT to the two-view FFDMs so that FFDM could be used for MC detection while DBT could be used for mass detection). This approach would increase imaging costs, reading time, and patient dose, which are all major concerns with regards to introducing DBT into clinical practice. The main goal of the proposed Partnership between the University of Michigan Computer-Aided Diagnosis Research Laboratory (UM) and GE Global Research (GE) is to develop an integrated practical approach to resolving the MC visualization and detection problems in DBT without increasing patient dose, thereby facilitating the eventual replacement of FFDM by DBT. To achieve this goal, we propose two Specific Aims: (SA1) to develop specially designed MC enhancing methods to improve human and machine visualization of MCs in DBT and develop a computer-aided detection (CAD) system to highlight significant MC clusters, and (SA2) to implement the developed MC-enhancing and CAD reading tools in a DBT workstation and conduct observer performance studies to compare MC detection in DBT with that in FFDM. The following tasks will be conducted to accomplish the specific aims: (1) perform phantom studies to determine the best set of image acquisition parameters for data collection, (2) collect a database of human subject DBTs for development of algorithms and observer study, (3) develop lesion-specific reconstruction and MC enhancing methods to improve the visibility of MCs in DBT for radiologist's reading and computerized detection, (4) develop computer-vision methods to detect MC candidates, (5) develop MC analysis method to reduce false positives (FPs) and insignificant CAD marks, (6) design two-view analysis to further reduce FPs, (7) study dependence of MC detection on reconstruction methods and tomosynthesis acquisition parameters, and (8) design a DBT workstation implemented with the MC-enhancing and CAD- assisted tools to highlight significant MCs for radiologist's reading. We hypothesize that the specially designed DBT display system can assist radiologists in detection of MCs in DBT with accuracy at least comparable to that in FFDM. To test this hypothesis, we will (9) conduct observer ROC studies to compare the detection accuracy of MCs under three conditions: (a) two-view DBT without CAD vs. two-view FFDM without CAD, (b) two-view DBT with CAD vs. two-view FFDM with CAD, and (c) a special protocol of CC-view FFDM plus MLO-view DBT with CAD vs. two-view FFDM with CAD.