Reengineering Workflow for Curation of DICOM Datasets
Reengineering Workflow for Curation of DICOM Datasets
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DOI：
10.1007/s10278-018-0097-4
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发表时间：
2018-12-01
影响因子：
4.4
通讯作者：
Bosch, Walter
中科院分区：
文献类型：
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作者：
Bennett, William;Smith, Kirk;Bosch, Walter
可重复使用、公开可用的数据是开放科学和癌症成像研究快速发展的支柱。共享已完成研究的数据不仅节省了收集数据所需的研究经费，而且有助于确保研究的可复制性和可再现性。癌症影像档案（TCIA）是一个全球共享的与癌症相关的影像数据存储库。确保存储在TCIA中的数据的一致性、科学性和匿名性至关重要。随着向TCIA提交DICOM对象存储的数量和复杂性的增加，集合的管理过程已经成为数据获取的瓶颈。为了提高图像集的整理速度，提高整理质量，并更好地跟踪提交的DICOM图像集的更改来源，开发了一套自定义工具，使用新的方法来分析DICOM数据集。这些工具使用perl编程语言编写，使用开源数据库PostgreSQL，利用开源包Posda中的perl DICOM例程，并从其他开源包（如dicom3tools）中合并DICOM诊断工具。这些工具被称为Posda工具。Posda工具是开源的，可以通过git访问https://github.com/UAMS-DBMI/PosdaTools获得。本文简要介绍了Posda工具，并讨论了这些工具为促进DICOM数据的快速分析所采用的新方法，包括：(1)使用一种更宽松的数据库模式，与传统的DICOM数据库进行了不同的规范化；(2)批量自动执行完整性检查；(3)通过基于web的界面或通过命令行可执行的perl脚本批量修改DICOM数据集；(4)所有此类编辑都在修订跟踪器中得到跟踪，并且可以回滚；(5)提供用户界面以检查该等编辑的结果，以核实其是否符合预期；(6)识别DICOM研究、系列和SOP实例，使用持久且具有明确定义范围的昵称，使DICOM错误报告的表达更容易管理；(7)利用像素数据快速识别潜在的重复DICOM数据集；例如，这可以用于识别可能与同一个人相关的提交主题，而无需识别个人。
Reusable, publicly available data is a pillar of open science and rapid advancement of cancer imaging research. Sharing data from completed research studies not only saves research dollars required to collect data, but also helps insure that studies are both replicable and reproducible. The Cancer Imaging Archive (TCIA) is a global shared repository for imaging data related to cancer. Insuring the consistency, scientific utility, and anonymity of data stored in TCIA is of utmost importance. As the rate of submission to TCIA has been increasing, both in volume and complexity of DICOM objects stored, the process of curation of collections has become a bottleneck in acquisition of data. In order to increase the rate of curation of image sets, improve the quality of the curation, and better track the provenance of changes made to submitted DICOM image sets, a custom set of tools was developed, using novel methods for the analysis of DICOM data sets. These tools are written in the programming language perl, use the open-source database PostgreSQL, make use of the perl DICOM routines in the open-source package Posda, and incorporate DICOM diagnostic tools from other open-source packages, such as dicom3tools. These tools are referred to as the Posda Tools. The Posda Tools are open source and available via git at https://github.com/UAMS-DBMI/PosdaTools. In this paper, we briefly describe the Posda Tools and discuss the novel methods employed by these tools to facilitate rapid analysis of DICOM data, including the following: (1) use a database schema which is more permissive, and differently normalized from traditional DICOM databases; (2) perform integrity checks automatically on a bulk basis; (3) apply revisions to DICOM datasets on an bulk basis, either through a web-based interface or via command line executable perl scripts; (4) all such edits are tracked in a revision tracker and may be rolled back; (5) a UI is provided to inspect the results of such edits, to verify that they are what was intended; (6) identification of DICOM Studies, Series, and SOP instances using nicknames which are persistent and have well-defined scope to make expression of reported DICOM errors easier to manage; and (7) rapidly identify potential duplicate DICOM datasets by pixel data is provided; this can be used, e.g., to identify submission subjects which may relate to the same individual, without identifying the individual.