A Biobanking System for Diagnostic Images: Architecture Development, COVID-19-Related Use Cases, and Performance...

Area of Science:

• Health Informatics
• Medical Imaging
• Biobanking

Background:

• Automated research and clinical data management systems are advancing healthcare.
• Imaging biobanks store diagnostic images, clinical reports, and demographic data.
• These biobanks facilitate research into lifestyle, genetics, and imaging phenotypes.

Purpose of the Study:

• To design and evaluate the network system performance of the Bio Check Up Srl (BCU) Imaging Biobank.
• To assess an operating biobank of diagnostic images using the Extensible Neuroimaging Archive Toolkit (ENIGMA).

Main Methods:

• Evaluated memory and computing consumption during image uploads and user interactions (researchers, radiologists).
• Tested three network setups: local area network (LAN), virtual private network (VPN), and wide area network (WAN).
• Recorded user activity replays, extracting network traffic and server log metrics.

Main Results:

• Web containers consumed more memory (2.7 GB RAM) than database containers.
• Both user types showed similar network performance.
• Specific actions had higher resource demands: DOWNLOAD & LOGOUT (researcher, 100%) and OPEN VIEWER (radiologist, 20%-50%).

Conclusions:

• The BCU Imaging Biobank setup adequately supports planned concurrent users.
• Quantified resource demands of user actions provide guidelines for system planning and usage.
• Highlights the importance of resource management in imaging biobanking.