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The digital imaging and communications in medicine (DICOM) protocol is the leading standard for image data management in healthcare. Imaging biomarkers and image-based surrogate endpoints in clinical trials and medical registries require DICOM viewer software with advanced functionality for visualization and interfaces for integration. In this paper, a comprehensive evaluation of 28 DICOM viewers is performed. The evaluation criteria are obtained from application scenarios in clinical research rather than patient care. They include (i) platform, (ii) interface, (iii) support, (iv) twodimensional (2D), and (v) three-dimensional (3D) viewing. On the average, 4.48 and 1.43 of overall 8 2D and 5 3D image viewing criteria are satisfied, respectively. Suitable DICOM interfaces for central viewing in hospitals are provided by GingkoCADx, MIPAV, and OsiriX Lite. The viewers ImageJ, MicroView, MIPAV, and OsiriX Lite offer all included 3D-rendering features for advanced viewing. Interfaces needed for decentral viewing in web-based systems are offered by Oviyam, Weasis, and Xero. Focusing on open source components, MIPAV is the best candidate for 3D imaging as well as DICOM communication. Weasis is superior for workflow optimization in clinical trials. Our evaluation shows that advanced visualization and suitable interfaces can also be found in the open source field and not only in commercial products.

Especially for investigator-initiated research at universities and academic institutions, Internet-based rare disease registries (RDR) are required that integrate electronic data capture (EDC) with automatic image analysis or manual image annotation. We propose a modular framework merging alpha-numerical and binary data capture. In concordance with the Office of Rare Diseases Research recommendations, a requirement analysis was performed based on several RDR databases currently hosted at Uniklinik RWTH Aachen, Germany. With respect to the study management tool that is already successfully operating at the Clinical Trial Center

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 multicenter 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.

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