CIDUR
CIDUR (Clinical Imaging Data for UR Researchers) is a web-based medical imaging data management system for the collection and governance of clinical imaging data for IRB-approved research. CIDUR is based on the open-source informatics platform XNAT and provides secure storage, access management, quality assessment, DICOM® image viewing, and de-identification tools.
Features
CIDUR is the enterprise solution for receiving and accessing imaging data in Digital Imaging and Communications in Medicine (DICOM) format from clinical imaging modalities such as magnetic resonance, x-ray, computed tomography, and ultrasound. CIDUR is approved to receive data directly from a clinical scanner or an imaging archive such as Picture Archiving and Communication System (PACS). This makes CIDUR a solution for prospective data collection through an IRB-approved protocol with consented subjects or for IRB-approved retrospective studies of existing clinical imaging data in the medical record system and PACS.
The UR CTSI Informatics and Analytics team supports investigators in setting up projects in CIDUR with governed workflows that align with their research needs and with patient privacy and security in mind. CIDUR features an integrated DICOM viewer, subject management tools, and dataset-cleaning capabilities. The API (Application Programming Interface) allows researchers to integrate CIDUR with downstream data analysis processes. The UR CTSI team offers select de-identification and patient anonymization capabilities to help researchers comply with IRB requirements and keep patient data safe.
Additional Features:
- Subject demographics management and integration with structured data
- Support for a wide range of imaging modalities
- Easy management of imaging data types with data structured in a patient, session, scan hierarchy
- Modular extensibility through plugins and containerization of computational processing
- Application Programming Interface (API) to query structured metadata and imaging data for analysis in external tools
- Python package for easy use of the API for data processing
- Robust and flexible role and group-based access controls
- Integrated OHIF DICOM viewer with image segmentation and measuring tools
- De-identification pipeline compliant with Supplement 142 and a select number of options
Get Started
To use CIDUR, users will need to be part of an IRB-approved protocol. Access is available from the URMC campus or via the URMC VPN while using a URMC Active Directory account with an active URMC email address.
The UR CTSI Informatics and Analytics team is happy to collaborate with you to support the clinical imaging data management needs of your project.
If you are planning a prospective, IRB-approved study using clinical imaging modalities, contact CIDUR_support@urmc.rochester.edu or fill out the project intake form to get started.
For retrospective studies and large-volume data requests from PACS or another imaging archive, contact the Informatics Consultation service of CTSI.
Get Training
Documentation is available on the CIDUR documents page. Information about XNAT, the open-source platform that CIDUR is built on, can be found on the official XNAT documentation page.
You can reach out to CIDUR_support@urmc.rochester.edu if you have questions.