An Open Source Digital Pathology System Supporting Multi-Touch Interaction

支持多点触控交互的开源数字病理系统

• 批准号: 8723822
• 负责人: Beverly Elizabeth Faulkner-Jones
• 金额: $ 74.67万
• 依托单位: KITWARE, INC.
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8723822
• 关键词: Academic Medical Centers; Address; Algorithms; Americas; Anatomy; Architecture; Arkansas; Atlases; Automatic Data Processing; Biopsy; Blood Tests; Charge; Client; Clinical Pathology; Collaborations; Collection; Communities; Computational Science; Computer software; Computers; Consensus; Consultations; Data; Data Set; Databases; Dermatology; Dermatopathology; Development; Diagnosis; Diagnostic; Differential Diagnosis; Distributed Databases; Education; Educational process of instructing; Endometrial; Fees; Foundations; Future; Generations; Genomics; Glass; Goals; Health; Healthcare; High Performance Computing; Image; Image Analysis; Imagery; Informatics; Ingestion; Institution; Intention; Internet; Journals; Knowledge; Lead; Light Microscope; Link; Maintenance; Medical; Medical Device; Medical Imaging; Medical Students; Medicine; Methods; New Mexico; Online Systems; Pathologist; Pathology; Patients; Performance; Phase; Physicians; Plug-in; Price; Process; Pythons; Radiology Specialty; Records; Research; Resolution; Retrieval; Running; Scanning; Secure; Services; Site; Slide; Social Network; Source; Support System; Surgical Pathology; System; Teaching Materials; Technology; Telepathology; Testing; Tissues; Touch sensation; Training; Training and Education; Trust; Universities; Validation; Washington; Work; base; computer framework; computerized tools; cost; data portal; data sharing; digital; distributed data; experience; handheld mobile device; image processing; improved; innovation; insight; medical schools; meetings; new technology; novel; open source; peer; prototype; public health relevance; tool; web page; web services; web site

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.

描述（由申请人提供）：本申请介绍了生物医学计算科学和技术计划中的创新，PAR-09-220。医疗保健正朝着完全数字化的患者记录迈进。手术病理学代表了一个挑战，因为与临床病理学（例如，血液测试）和放射学相比，载玻片上组织截面的高分辨率成像会产生大的数据集。此外，FDA最近宣布打算将整个幻灯片扫描仪作为III类医疗设备进行调节，从而延迟了用于主要诊断的数字病理学的实施。然而，数字病理学在其他应用中具有巨大的潜力，包括教育（医师居民和医学生的教学和培训），次要咨询诊断和研究。而且，越来越多的感觉是，数字方法的应用可以彻底改变解剖病理学中的诊断，就像基因组技术被预测会彻底改变临床病理学的诊断。尽管目前尤其是医学界，尤其是解剖学家，尤其是在适应新技术方面的速度很慢，但在不久的将来，病理学可能会带头通过精确医学改善诊断（即分析 大型多部分健康数据集）。 我们的第一阶段努力专注于开发高性能，开源，客户服务器系统，用于远程查看整个幻灯片图像。我们成功的原型系统每周都用于哈佛大学病理学和皮肤病学居民的皮肤病理学教学，并将在圣路易斯华盛顿大学和新墨西哥大学使用。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以及远程协作查看和交互的点对点数据共享。我们将提供一个开放的数据存储库，供用户上传和共享他们的图像，并在第1阶段收集的6,000多个图像上开发其他内容。进一步我们将促进创新并扩展我们的开放，敏捷的体系结构，以支持插件支持分析模块（例如，支持CAD）（以支持CAD），并通过使用开放式图像分析工具工具工具Kit Kitk。最后，通过使用试点挑战研究，我们将开始量化早期的轶事证据，表明数字病理系统更快，并且在某些应用中比使用物理幻灯片的常规方法更好。 我们的目标是建立对系统（服务器软件）和/或服务（用于上传和查看图像的Web门户）的广泛使用以创建大型病理网络。在拟议的为期两年的第二阶段中，我们将部署该软件并为合作机构提供服务（目前有六个）。此外，Co-Pi Faulkner-Jones博士将开发一个精选的幻灯片图像收集 这将建立在当前值得信赖的高需求内容的基础上。