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Radiologists interpreting knee MRI studies must assess multiple structures, including cartilage, menisci, and ligaments, often across complex anatomical regions. To support this process, mdknee, an AI solution developed by mediaire, is now available through the deepcOS® platform.
Musculoskeletal MRI volumes continue to grow, placing increasing pressure on radiologists to evaluate joint structures efficiently and consistently. Knee MRI interpretation requires a detailed assessment of several anatomical regions, where subtle abnormalities such as cartilage lesions, ligament injuries, or meniscal damage may be difficult to detect consistently, particularly in high-volume musculoskeletal imaging workflows.
mdknee assists radiologists by automatically detecting and classifying structural abnormalities in knee MRI studies. The solution analyzes imaging data to identify damage affecting cartilage, menisci, and major ligaments, including the ACL, MCL, and LCL. Findings are mapped across more than 24 anatomical zones, providing a structured overview of the joint and supporting consistent interpretation across cases.
Detected abnormalities are presented through visual overlays directly on MRI images alongside structured report outputs. Color-coded indicators highlight suspected findings while preserving full visibility of the underlying imaging data. Cartilage damage is also graded using the ICRS (International Cartilage Repair Society) classification system, enabling standardized documentation of lesion severity.
Beyond identifying potential abnormalities, structured outputs organize findings by anatomical location and severity, supporting clearer communication with referring clinicians and helping reduce variability in reporting across readers and institutions.
Through integration with deepcOS®, healthcare organizations can access mdknee within their existing radiology environments. AI results appear directly within routine diagnostic workflows, allowing radiologists to review AI-supported findings without switching to separate software environments.
mdknee is a CE-marked Class IIb medical device, certified by TÜV SÜD Product Service GmbH, and is intended for the automated labeling, visualization, and quantification of knee MRI data.
The addition of mdknee broadens the range of AI solutions available through deepcOS®, providing healthcare providers with additional tools designed to support musculoskeletal imaging workflows.
