???MammoTutor: An Internet-Based Computer Tutoring System to Teach General Radiol

???MammoTutor：基于互联网的计算机辅助系统，教授一般放射学知识

• 批准号: 7784804
• 负责人: CLAUDIA R MELLO-THOMS
• 金额: $ 10.48万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7784804
• 关键词: MammoTutor; Internet; Based; Computer; Tutoring

DESCRIPTION (Provided by Applicant): Breast cancer is the most common cancer among women worldwide, and the second leading cause of cancer-related deaths among this population in the United States. As with many other types of cancer, early detection can have a significant impact in patient prognosis, and the recommendation of mammography screening to the general women population older than 40 years of age has saved thousands of lives. However, the reading of a mammogram is a very complex perceptual and cognitive task, and the applicant has previously shown that, under the current training guidelines, at the end of their residency, novice radiologists are no better at detecting breast cancer than breast technologists, who do not receive any formal training in how to detect this disease. Moreover, a fraction of these novice radiologists will become generalists, namely, they will be board certified to read a lot of different images, including mammograms. The lack of specialized training in breast imaging is reflected in the performance of these general radiologists, who not only detect fewer breast cancers but also detect fewer early-staged breast lesions when compared to better trained breast radiologists. This problem is acute amongst African-American women, who, in general, due to socio-economical status, receive their mammograms at community-based centers or at outreach clinics, facilities that tend to be staffed by general radiologists. In this project we propose to build upon the framework of a previously designed and evaluated computer-based tutoring system, named SlideTutor, which has been developed for another visual domain within Medicine, namely, Pathology. In that domain, use of SlideTutor has been shown to produce significant improvements in diagnostic reasoning among novice pathologists, and retention of the learned material has been observed over time. Thus, it is our goal to use a similar framework to develop a computer-based cognitive tutoring system that can teach generalists and novice radiologists (i) how to detect early-staged breast cancer (thus yielding improvements in overall sensitivity); and (ii) how to reduce the number of unnecessary biopsy recommendations (therefore improving specificity). Hence, it is our hypothesis that use of cognitive tutoring will. If successful, such intervention should have a significant impact in health care delivery to socio-economically disadvantage populations, and to reduce health care disparities between minority populations (such as African-Americans) and more affluent populations. In addition, in order to reach as wide a number of radiologists as possible, our computer-based tutoring system will be placed on the Internet, where it will be available, free of charge, to any radiologists who register to receive training in this task. Currently, the missed rates at mammography screenings are between 10 and 30 percent. In this project, we will develop a computer based tutoring system to train radiologists how to detect early signs of breast cancer. Our system will be deployed over the internet and will be available free of charge.

描述（由申请人提供）：乳腺癌是全球妇女中最常见的癌症，也是美国该人群中与癌症相关的第二大原因。与许多其他类型的癌症一样，早期发现可能会对患者预后产生重大影响，并且对40岁以上的一般妇女人口进行乳房X线摄影筛查的建议挽救了数千人的生命。然而，乳房X线照片的阅读是一项非常复杂的感知和认知任务，并且申请人先前表明，在当前的训练指南下，在其居住期结束时，新手放射科医生在检测乳腺癌方面没有比乳腺癌更好的乳腺癌，而乳腺癌没有接受任何在如何识别这种疾病方面接受任何正式训练。此外，这些新手放射科医生中的一部分将成为通才，即，他们将获得董事会认证，可以阅读许多不同的图像，包括乳房X线照片。与训练有素的乳房放射科医生相比，这些普通放射科医生的表现不足，缺乏乳房成像的专业训练反映在这些普通放射科医生的表现中，而且发现较少的早期乳腺病变。这个问题在非裔美国妇女中很严重，通常由于社会经济地位，她们在社区中心或外展诊所接受了乳房X光检查，这些设施往往由普通放射科医生组成。在这个项目中，我们建议建立在先前设计和评估的基于计算机的辅导系统的框架上，该系统名为Slidetutor，该系统已为医学中的另一个视觉领域开发，即病理学。在该领域，已显示使用滑块可以在新手病理学家之间产生诊断推理的显着改善，并且随着时间的推移，已经观察到了学习材料的保留。因此，我们的目标是使用类似的框架来开发基于计算机的认知辅导系统，该系统可以教授通才和新手放射科医生（i）如何检测早期乳腺癌（从而提高了整体敏感性）； （ii）如何减少不必要的活检建议的数量（从而提高特异性）。因此，我们的假设是使用认知辅导意愿。如果成功的话，这种干预措施将对在社会经济上不利的人群中提供重大影响，并减少少数民族人口（例如非裔美国人）和更多富裕人群之间的医疗保健差异。此外，为了达到尽可能宽的放射科医生，我们的基于计算机的辅导系统将放在互联网上，该系统将免费提供给任何放射科医生，这些放射科医生注册以接受此任务的培训。目前，乳房X线摄影检查的错率在10％至30％之间。在这个项目中，我们将开发一个基于计算机的补习系统，以培训放射科医生如何检测乳腺癌的早期迹象。我们的系统将通过Internet部署，并将免费提供。