Biomedical Imaging Research Group (GIBI(230)-PREBI) at La Fe Health Research Institute and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.
Biomedical Imaging Research Group (GIBI(230)-PREBI) at La Fe Health Research Institute and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.
Int J Med Inform. 2024 Oct;190:105549. doi: 10.1016/j.ijmedinf.2024.105549. Epub 2024 Jul 14.
We present the needs, design, development, implementation, and accessibility of a crafted experimental PACS (ePACS) system to securely store images, ensuring efficiency and ease of use for AI processing, specifically tailored for research scenarios, including phantoms, animal and human studies and quality assurance (QA) exams. The ePACS system plays a crucial role in any medical imaging departments that handle non-care profile studies, such as protocol adjustments and dummy runs. By effectively segregating non-care profile studies from the healthcare assistance, the ePACS usefully prevents errors both in clinical practice and storage security.
The developed ePACS system considers the best practices for management, maintenance, access, long-term storage and backups, regulatory audits, and economic aspects. Moreover, key aspects of the ePACS system include the design of data flows with a focus on incorporating data security and privacy, access control and levels based on user profiles, internal data management policies, standardized architecture, infrastructure and application monitorization and traceability, and periodic backup policies. A new tool called DicomStudiesQA has been developed to standardize the analysis of DICOM studies. The tool automatically identifies, extracts, and renames series using a consistent nomenclature. It also detects corrupted images and merges separated dynamic series that were initially split, allowing for streamlined post-processing.
The developed ePACS system encompasses a successful implementation, both in hospital and research environments, showcasing its transformative nature and the challenging yet crucial transfer of knowledge to industry. This underscores the practicality and real-world applicability of our innovative approach, highlighting the significant impact it has on the field of experimental radiology.
我们介绍了一个精心制作的实验性 PACS（ePACS）系统的需求、设计、开发、实施和可访问性，该系统旨在安全地存储图像，确保人工智能处理的效率和易用性，特别针对研究场景进行了定制，包括体模、动物和人体研究以及质量保证（QA）检查。ePACS 系统在处理非护理档案研究的任何医学影像部门中都起着至关重要的作用，例如协议调整和模拟运行。通过有效地将非护理档案研究与医疗保健援助分开，ePACS 有助于防止临床实践和存储安全中的错误。
开发的 ePACS 系统考虑了管理、维护、访问、长期存储和备份、法规审计以及经济方面的最佳实践。此外，ePACS 系统的关键方面包括数据流的设计，重点是纳入数据安全和隐私、访问控制以及基于用户配置文件的级别、内部数据管理策略、标准化架构、基础设施和应用程序监测和可追溯性，以及定期备份策略。还开发了一个名为 DicomStudiesQA 的新工具，用于标准化 DICOM 研究的分析。该工具使用一致的命名约定自动识别、提取和重命名系列。它还可以检测损坏的图像并合并最初分开的动态系列，从而实现简化的后处理。
开发的 ePACS 系统在医院和研究环境中都实现了成功实施，展示了其变革性的性质以及向工业界转移知识的挑战性和至关重要性。这强调了我们创新方法的实用性和实际应用，突出了它对实验放射学领域的重大影响。
