Moscow has integrated a new artificial intelligence service into its healthcare system to identify signs of hip osteoarthritis in medical images, marking the 41st modality where neural networks assist radiologists. This advancement was announced by Anastasia Rakova, Deputy Mayor of Moscow for Social Development.
Developed and tested by specialists at the Center for Diagnostics and Telemedicine, the AI algorithm has completed rigorous testing and is now integrated into the Unified Radiological Information Service (URIS). “The algorithm automatically identifies potential osteoarthritis indicators – such as joint space narrowing, bone thickening, and bone spur highlighting affected areas and performing precise measurements”, she stated.
“Moscow now utilizes AI across 40 clinical modalities. These innovations accelerate diagnosis, improve accuracy, and reduce the workload for radiologists”.
Osteoarthritis (OA) is a chronic joint disorder characterized by progressive cartilage degradation and bone remodeling. While prevalent among older adults, it can occur at any age. A new AI service deployed in Moscow assists radiologists in identifying key indicators of hip OA, including joint space narrowing, subchondral sclerosis (bone thickening), and osteophyte formation. This automation reduces image interpretation time, enhances diagnostic accuracy, and enables earlier therapeutic intervention.
“The AI service enhances early detection of hip arthrosis, enabling timely treatment and better patient outcomes.”
Yuri Vasilev, Moscow’s Chief Consultant for Radiology of the Moscow Healthcare Department, emphasized the clinical impact: “Accurate imaging assessment of hip osteoarthritis allows precise staging of hip OA, informing treatment strategies such as activity recommendations and pharmacotherapy. Key clinical signs of osteoarthritis include pain during ambulation and reduced range of motion in affected joints.”
This AI deployment builds on five years of Moscow’s pioneering efforts to integrate computer vision in healthcare. Over 200 AI services have been tested, with approximately 100 algorithms incorporated into the URIS UMIAS system. Currently, around 50 AI tools analyze medical images in real-time, improving diagnostic speed and quality across 40 clinical modalities.
The project is a collaboration between the Moscow Social Development Complex, the Center for Diagnostics and Telemedicine, and the city Department of Information Technology, underscoring Moscow’s commitment to leveraging AI for enhanced medical care.