Comprehensive Redaction for Neurological Imaging

描述（由申请人提供）：在神经科学中，由于对神经影像数据集中个人健康信息（PHI）的管理和处理的担忧，大规模协作和数据共享的潜力严重不足。 特别是，HIPAA和HITECH规则要求采取实质性措施保护受试者隐私。 对于以科学为中心的研究者来说，信息隐私的管理是一项非常繁重的任务。 研究中神经影像的共享和Meta分析的巨大潜力由于两个原因而未得到实现：（i）系统的清理受到缺乏从DICOM图像中系统地删除PHI的工具的阻碍，以及（ii）将清理集成到数据共享过程中的既定工作流程仍然明显缺乏。 该提案旨在通过增强用于管理和共享神经影像的已建立和流行的软件框架-可扩展神经影像存档工具包（XNAT）-以及用于编辑DICOM图像文件中的PHI的工具集和集成工作流程来解决这两个挑战。 这项工作所涉及的编辑过程与简单的清理技术不同，因为它使用隐私映射数据库中的匿名标识符来消除主题之间的歧义，而不跟踪他们的身份。 这种方法为研究人员提供了共享神经影像数据集的最大能力和灵活性，同时在标准化数据管理过程中透明地处理PHI考虑因素。 建议的编辑工具集补充了XNAT中的数据策展和管理工具，并在现有的XNAT操作工作流程和实验室流程中整齐地折叠。 工具集和工作流程坚持心理可接受性和最小特权的安全设计原则，促进广泛的用户采用并确保受试者的机密性。 消毒过程本身建立在法律的编辑原则和证据规则的基础上，为科学家和调查人员提供了更高水平的保证，以符合HIPAA。 该项目的长期目标是创建一个全面实用的基础设施，用于管理神经影像数据集中的PHI，并减轻研究人员在数据清理和编辑技术方面的负担。 通过这样做，这一努力将消除神经科学中大规模合作和数据共享的重大障碍。 公共卫生相关性：在神经科学中，由于对神经影像数据集中的个人健康信息（PHI）的管理和处理的担忧，大规模协作和数据共享的潜力严重不足。 本提案旨在通过使用DICOM图像文件中PHI匿名编辑的工具集和集成工作流增强可扩展神经影像存档工具包（XNAT）来解决此问题。 这项工作所采用的方法为研究人员提供了共享神经影像数据集的最大能力和灵活性，同时在标准化数据管理过程中透明地处理PHI考虑因素。

DESCRIPTION (provided by applicant): In neuroscience, the potential for large scale collaboration and data sharing is seriously under- mined by concerns over the management and handling of personal health information (PHI) in neuroimagery data sets. In particular, HIPAA and HITECH rules mandate substantial measures for the preservation of subject privacy. For the researcher, whose focus is on the science, the management of information privacy is a wholly burdensome task. The vast potential for sharing and meta analysis of neuroimagery in research goes unfulfilled for two reasons: (i) systematic sanitization is hampered by the dearth of tools to systematically expunge PHI from DICOM images, and (ii) an established workflow that integrates sanitization into the data sharing process remains conspicuously absent. This proposal seeks to address both of these challenges by augmenting an established and popular software framework for managing and sharing neuroimagery - the Extensible Neuroimaging Archive Toolkit (XNAT) - with a toolset and integrated workflow for redaction of PHI in DICOM image files. The redaction process to be engaged by this effort differs from naive sanitization tech- niques in that it uses pseudonymous identifiers in a Privacy Mapping Database to disambiguate between subjects without tracking their identities. This approach gives researchers the maximum power and flexibility in sharing neuroimagery datasets, while transparently coping with PHI considerations in a standardized data curation process. The proposed redaction toolset complements the data curation and management tools within XNAT and folds neatly within existing XNAT operational workflows and lab processes. The toolset and workflow adhere to the secure design principles of psychological acceptability and least privilege, promoting broad user adoption and ensuring subject confidentiality. The sanitization process itself is built upon principles of legal redaction and rules of evidence, providing heightened levels of assurance for scientists and investigators for HIPAA compliance. The long term objectives of this project are to create a comprehensive and practical infrastructure for managing PHI in neuroimagery datasets, and to relieve the burden of the investigator from the technical aspects of data sanitization and redaction. In so doing, this effort will remove substantial obstacles to large-scale collaboration and data sharing in neuroscience. PUBLIC HEALTH RELEVANCE: In neuroscience, the potential for large scale collaboration and data sharing is seriously under- mined by concerns over the management and handling of personal health information (PHI) in neuroimagery data sets. This proposal seeks to address this problem by augmenting the Extensi- ble Neuroimaging Archive Toolkit (XNAT) with a toolset and integrated workflow for pseudonymous redaction of PHI in DICOM image files. The approach adopted by this effort gives researchers the maximum power and flexibility in sharing neuroimagery datasets, while transparently coping with PHI considerations in a standardized data curation process.