Department of Psychiatry, University of California at San Diego, San Diego, CA, USA.
Neuroinformatics. 2010 Dec;8(4):231-49. doi: 10.1007/s12021-010-9078-6.
Managing vast datasets collected throughout multiple clinical imaging communities has become critical with the ever increasing and diverse nature of datasets. Development of data management infrastructure is further complicated by technical and experimental advances that drive modifications to existing protocols and acquisition of new types of research data to be incorporated into existing data management systems. In this paper, an extensible data management system for clinical neuroimaging studies is introduced: The Human Clinical Imaging Database (HID) and Toolkit. The database schema is constructed to support the storage of new data types without changes to the underlying schema. The complex infrastructure allows management of experiment data, such as image protocol and behavioral task parameters, as well as subject-specific data, including demographics, clinical assessments, and behavioral task performance metrics. Of significant interest, embedded clinical data entry and management tools enhance both consistency of data reporting and automatic entry of data into the database. The Clinical Assessment Layout Manager (CALM) allows users to create on-line data entry forms for use within and across sites, through which data is pulled into the underlying database via the generic clinical assessment management engine (GAME). Importantly, the system is designed to operate in a distributed environment, serving both human users and client applications in a service-oriented manner. Querying capabilities use a built-in multi-database parallel query builder/result combiner, allowing web-accessible queries within and across multiple federated databases. The system along with its documentation is open-source and available from the Neuroimaging Informatics Tools and Resource Clearinghouse (NITRC) site.
管理来自多个临床成像社区的庞大数据集已成为当务之急，因为数据集的数量不断增加且种类繁多。数据管理基础设施的开发还因技术和实验的进步而变得更加复杂，这些进步推动了对现有协议的修改，并获取了新类型的研究数据，以纳入现有的数据管理系统。本文介绍了一种用于临床神经影像学研究的可扩展数据管理系统：人类临床成像数据库（HID）和工具包。该数据库模式的构建支持存储新的数据类型，而无需更改基础架构。复杂的基础架构允许管理实验数据，例如图像协议和行为任务参数，以及特定于主题的数据，包括人口统计学、临床评估和行为任务性能指标。值得关注的是，嵌入式临床数据录入和管理工具增强了数据报告的一致性，并自动将数据录入数据库。临床评估布局管理器（CALM）允许用户为内部和跨站点创建在线数据录入表单，通过通用临床评估管理引擎（GAME）将数据拉到基础数据库中。重要的是，该系统旨在在分布式环境中运行，以面向服务的方式为人类用户和客户端应用程序提供服务。查询功能使用内置的多数据库并行查询构建器/结果组合器，允许在多个联合数据库中进行基于 Web 的查询。该系统及其文档是开源的，可从神经影像学信息学工具和资源知识库（NITRC）站点获得。
