Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.
Enovacom, Marseille, France.
Stud Health Technol Inform. 2022 Jun 6;290:27-31. doi: 10.3233/SHTI220025.
Clinical image data analysis is an active area of research. Integrating such data in a Clinical Data Warehouse (CDW) implies to unlock the PACS and RIS and to address interoperability and semantics issues. Based on specific functional and technical requirements, our goal was to propose a web service (I4DW) that allows users to query and access pixel data from a CDW by fully integrating and indexing imaging metadata. Here, we present the technical implementation of this workflow as well as the evaluation we carried out using a prostate cancer cohort use case. The query mechanism relies on a Dicom metadata hierarchy dynamically generated during the ETL Process. We evaluated the Dicom data transfer performance of I4DW, and found mean retrieval times of 5.94 seconds and 0.9 seconds to retrieve a complete DICOM series from the PACS and all metadata of a series. We could retrieve all patients and imaging tests of the prostate cancer cohort with a precision of 0.95 and a recall of 1. By leveraging the CMOVE method, our approach based on the Dicom protocol is scalable and domain-neutral. Future improvement will focus on performance optimization and de identification.
临床影像数据分析是一个活跃的研究领域。将此类数据集成到临床数据仓库(CDW)中意味着要解锁 PACS 和 RIS,并解决互操作性和语义问题。基于特定的功能和技术要求,我们的目标是提出一个 Web 服务(I4DW),通过充分集成和索引成像元数据,允许用户从 CDW 查询和访问像素数据。在这里,我们介绍了该工作流程的技术实现,以及我们使用前列腺癌队列用例进行的评估。查询机制依赖于 ETL 过程中动态生成的 Dicom 元数据层次结构。我们评估了 I4DW 的 Dicom 数据传输性能,发现从 PACS 检索完整的 DICOM 系列和系列的所有元数据的平均检索时间分别为 5.94 秒和 0.9 秒。我们可以检索前列腺癌队列的所有患者和影像学检查,精确率为 0.95,召回率为 1。通过利用 CMOVE 方法,我们基于 Dicom 协议的方法具有可扩展性和领域中立性。未来的改进将集中在性能优化和去识别化。