Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
University of Iowa, Iowa City, IA.
JCO Clin Cancer Inform. 2020 May;4:444-453. doi: 10.1200/CCI.19.00165.
We summarize Quantitative Imaging Informatics for Cancer Research (QIICR; U24 CA180918), one of the first projects funded by the National Cancer Institute (NCI) Informatics Technology for Cancer Research program.
QIICR was motivated by the 3 use cases from the NCI Quantitative Imaging Network. 3D Slicer was selected as the platform for implementation of open-source quantitative imaging (QI) tools. Digital Imaging and Communications in Medicine (DICOM) was chosen for standardization of QI analysis outputs. Support of improved integration with community repositories focused on The Cancer Imaging Archive (TCIA). Priorities included improved capabilities of the standard, toolkits and tools, reference datasets, collaborations, and training and outreach.
Fourteen new tools to support head and neck cancer, glioblastoma, and prostate cancer QI research were introduced and downloaded over 100,000 times. DICOM was amended, with over 40 correction proposals addressing QI needs. Reference implementations of the standard in a popular toolkit and standalone tools were introduced. Eight datasets exemplifying the application of the standard and tools were contributed. An open demonstration/connectathon was organized, attracting the participation of academic groups and commercial vendors. Integration of tools with TCIA was improved by implementing programmatic communication interface and by refining best practices for QI analysis results curation.
Tools, capabilities of the DICOM standard, and datasets we introduced found adoption and utility within the cancer imaging community. A collaborative approach is critical to addressing challenges in imaging informatics at the national and international levels. Numerous challenges remain in establishing and maintaining the infrastructure of analysis tools and standardized datasets for the imaging community. Ideas and technology developed by the QIICR project are contributing to the NCI Imaging Data Commons currently being developed.
总结美国国立癌症研究所(NCI)信息学技术癌症研究计划资助的第一个项目之一——癌症研究的定量成像信息学(QIICR;U24 CA180918)。
QIICR 的动机来自 NCI 定量成像网络的 3 个用例。选择 3D Slicer 作为实现开源定量成像(QI)工具的平台。选择数字成像和通信医学(DICOM)来标准化 QI 分析输出。支持与专注于癌症成像档案(TCIA)的社区存储库的改进集成是重点。优先事项包括提高标准、工具包和工具、参考数据集、合作以及培训和推广的能力。
引入了 14 种新工具,以支持头颈部癌症、胶质母细胞瘤和前列腺癌的 QI 研究,下载量超过 10 万次。DICOM 得到了修订,提出了 40 多个纠正提案以满足 QI 需求。在流行的工具包和独立工具中引入了该标准的参考实现。贡献了 8 个数据集,展示了该标准和工具的应用。组织了一次开放演示/连接活动,吸引了学术团体和商业供应商的参与。通过实现程序通信接口和改进 QI 分析结果管理的最佳实践,提高了工具与 TCIA 的集成。
我们引入的工具、DICOM 标准的功能和数据集在癌症成像社区中得到了采用和应用。协作方法对于解决国家和国际层面的成像信息学挑战至关重要。在为成像社区建立和维护分析工具和标准化数据集的基础设施方面仍然存在许多挑战。QIICR 项目开发的想法和技术正在为当前正在开发的 NCI 成像数据 Commons 做出贡献。