DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials
| Autor: | Thilo Krüger, Daniel Haak, Sebastian Reinartz, Charles-E. Page, Thomas Martin Deserno |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Radiological and Ultrasound Technology
Electronic data capture Multimedia Database Computer science business.industry Context (language use) Communications system computer.software_genre Article Workflow Computer Science Applications Systems Integration DICOM Radiology Information Systems Picture archiving and communication system Medical imaging Humans Multicenter Studies as Topic System integration Radiology Nuclear Medicine and imaging Tomography X-Ray Computed business computer |
| Zdroj: | Journal of Digital Imaging. 28:558-566 |
| ISSN: | 1618-727X 0897-1889 |
| DOI: | 10.1007/s10278-015-9802-8 |
| Popis: | Providing surrogate endpoints in clinical trials, medical imaging has become increasingly important in human-centered research. Nowadays, electronic data capture systems (EDCS) are used but binary image data is integrated insufficiently. There exists no structured way, neither to manage digital imaging and communications in medicine (DICOM) data in EDCS nor to interconnect EDCS with picture archiving and communication systems (PACS). Manual detours in the trial workflow yield errors, delays, and costs. In this paper, requirements for a DICOM-based system interconnection of EDCS and research PACS are analysed. Several workflow architectures are compared. Optimized for multi-center trials, we propose an entirely web-based solution integrating EDCS, PACS, and DICOM viewer, which has been implemented using the open source projects OpenClinica, DCM4CHEE, and Weasis, respectively. The EDCS forms the primary access point. EDCS to PACS interchange is integrated seamlessly on the data and the context levels. DICOM data is viewed directly from the electronic case report form (eCRF), while PACS-based management is hidden from the user. Data privacy is ensured by automatic de-identification and re-labelling with study identifiers. Our concept is evaluated on a variety of 13 DICOM modalities and transfer syntaxes. We have implemented the system in an ongoing investigator-initiated trial (IIT), where five centers have recruited 24 patients so far, performing decentralized computed tomography (CT) screening. Using our system, the chief radiologist is reading DICOM data directly from the eCRF. Errors and workflow processing time are reduced. Furthermore, an imaging database is built that may support future research. |
| Databáze: | OpenAIRE |
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