An Open Source Digital Pathology System Supporting Multi-Touch Interaction

描述（由申请人提供）：本申请涉及生物医学计算科学和技术计划PAR-09-220的创新。医疗保健正在向完全数字化的患者记录迈进。手术病理学代表了一种挑战，因为载玻片上的组织切片的高分辨率成像产生的数据集与临床病理学的数据集相比是大的（例如，血液检查）和放射学。此外，FDA最近宣布打算将全载玻片扫描仪作为III类医疗设备进行监管，推迟了数字病理学在初级诊断中的实施。然而，数字病理学在其他应用中具有巨大的潜力，包括教育（住院医师和医学生的教学和培训），二级咨询诊断和研究。更重要的是，人们越来越意识到，数字方法的应用可以彻底改变解剖病理学的诊断，就像基因组学技术被预测会彻底改变临床病理学的诊断一样。尽管医学界，特别是解剖病理学家目前在适应新技术方面进展缓慢，但在不久的将来，病理学可能会通过精确医学（即，分析的 大型多部分健康数据集）。 我们的第一阶段工作重点是开发一个高性能、开源的客户端-服务器系统，用于远程查看整个幻灯片图像。我们成功的原型系统已被用于每周教学的皮肤病理学的居民在病理学和皮肤病学在哈佛大学，并将在华盛顿大学圣路易斯和在新墨西哥州的大学。对于第二阶段，我们建议扩展客户端-服务器系统，以支持分布式数据库中的对等数据共享，以及远程协作查看和交互。我们将为用户提供一个开放的数据存储库，供他们上传和分享他们的图像，并在第一阶段收集的6,000多张图像上开发更多内容。此外，我们将促进创新，并扩展我们的开放、敏捷架构，以支持分析模块的插件支持（例如，以支持CAD），并通过使用开源医学图像分析工具包ITK来演示此功能。最后，通过使用试点挑战研究，我们将开始量化早期轶事证据，即数字病理学系统在某些应用中比使用物理载玻片的传统方法更快，并提供更好的结果。 我们的目标是建立系统（服务器软件）和/或服务（用于上传和查看图像的门户网站）的广泛使用，以创建一个大型病理学网络。在拟议的两年第二阶段，我们将向伙伴机构（目前有六个）部署软件和支持服务。此外，联合PI博士福克纳-琼斯将开发一个策划的幻灯片图像集 这将建立在目前收集的可信的，高需求的内容。

DESCRIPTION (provided by applicant): This application addresses Innovations in Biomedical Computational Science and Technology Initiative PAR-09-220. Healthcare is moving towards fully digitized patient records. Surgical pathology represents a challenge in that high resolution imaging of tissue sections on glass slides produces datasets that are large compared to those of clinical pathology (e.g., blood tests) and radiology. Moreover the FDA recently announced its intention to regulate whole slide scanners as Class III medical devices, delaying implementation of digital pathology for primary diagnosis. Nevertheless digital pathology has enormous potential in other applications including education (teaching and training of physician residents and medical students), secondary consultation diagnosis and research. What is more there is a growing sense that application of digital methods can revolutionize diagnostics in anatomic pathology just as genomics technologies are predicted to revolutionize diagnostics in clinical pathology. Although the medical profession in general and anatomic pathologists in particular are currently seen to be slow in adapting the new technology, in the very near future pathology likely will take the lead in improving diagnosis through precision medicine (i.e., analytics of the large multi-part health datasets). Our Phase I efforts were focused on developing a high performance, open-source, client-server system for remote viewing of whole slide images. Our successful prototype system has been used weekly for teaching of Dermatopathology to residents in pathology and dermatology at Harvard University, and will be used at Washington University in St. Louis and at the University of New Mexico. For Phase II we are proposing to extend the client-server system to support peer-to-peer data sharing across a distributed database, and remote collaborative viewing and interaction. We will provide an open data repository for users to upload and share their images, and develop additional content on the 6,000 plus images already gathered in Phase I. Further we will promote innovation and extend our open, agile architecture to support plug-in support for analysis modules (e.g., to support CAD) and demonstrate this capability by using the open-source, medical image analysis toolkit ITK. Finally, through the use of a pilot Challenge Study we will begin to quantify early anecdotal evidence that the digital pathology system is faster and provides better results in certain applications than conventional approaches using physical slides. Our goal is to establish widespread use of the system (server software) and/or service (web portal for uploading and viewing images) to create a large pathology network. During the proposed two-year Phase II we will deploy the software and support the services to partnering institutions (there are six currently). In addition, the co-PI Dr. Faulkner-Jones will develop a curated slide image collection that will build on the current collection of trusted, high-demand content.