RBknee
Radiobotics ApSRBknee is an AI-powered software that automatically analyzes knee X-ray images to measure joint space width and assess signs of knee osteoarthritis. It provides objective measurements and standardized grading to help medical professionals in evaluating knee osteoarthritis severity, supporting diagnosis and treatment decisions.
Intended Use
RBknee is a fully automated software device intended to aid medical professionals in measuring minimum joint space width and assessing the presence or absence of sclerosis, joint space narrowing, osteophytes based on OARSI criteria, and radiographic knee osteoarthritis based on Kellgren-Lawrence grading from standing fixed-flexion radiographs of the knee.
Technology
RBknee utilizes computer vision and machine learning algorithms trained on medical X-ray images to detect and measure osteoarthritis-related features. It outputs visual overlays on radiographs and textual reports including measurements and standardized grading scores. It runs as standalone software compatible with Linux and Docker, and can integrate with PACS and DICOM viewers.
Performance
Software verification and validation testing confirmed intended function. Clinical performance was validated on a large osteoarthritis image dataset (Osteoarthritis Initiative) showing high sensitivity and specificity for detection of Kellgren-Lawrence grade, joint space narrowing, osteophytes, and sclerosis, as well as high accuracy in measuring minimum joint space width compared to expert readings.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
12/18/2020
8 months - 2
FDA Approval
8/27/2021
Ready to Sharpen Your Edge?
Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.
We respect your privacy. Unsubscribe at any time.