Groundbreaking AI Tool to Protect Young Hips
Researchers from the Universities of Manchester and Liverpool, in collaboration with Manchester Imaging Ltd, have unveiled an automatic tool designed to prevent hip dislocation in children living with cerebral palsy (CP). The project, backed by a £1.2 million grant from the National Institute for Health and Care Research (NIHR), marks a significant step forward in personalized care for CP patients and could change how clinicians monitor and treat hip health in young people.
Why Hip Dislocation Matters in Cerebral Palsy
Cerebral palsy affects movement and muscle tone, which can increase the risk of the hip joint becoming dislocated. This complication not only causes pain and reduced mobility but can also lead to long-term complications if not detected early. Early intervention, regular monitoring, and tailored therapies are key to maintaining hip stability and quality of life for affected children.
The Science Behind the Automatic Tool
The new system leverages artificial intelligence to analyse imaging data and clinical information to identify subtle indicators of hip instability long before overt dislocation occurs. By integrating with routine imaging workflows, the tool aims to provide clinicians with a proactive alert system and individualized risk assessments. The approach combines machine learning with biomechanical modeling to interpret complex signals from X-ray and MRI datasets that are typical in paediatric orthopaedic care.
What the Tool Will Do for Clinicians and Families
Early, accurate prediction of hip risk can guide decisions about therapy, seating, positioning, and potential surgical planning. For families, this means clearer information about prognosis, more consistent monitoring schedules, and targeted interventions that aim to preserve hip function as children grow. The tool is designed to integrate smoothly into existing clinics, with an emphasis on ease of use and patient safety.
Collaboration and Funding Driving Innovation
The Manchester and Liverpool teams bring together expertise in paediatric orthopedics, radiology, and AI development. Manchester Imaging Ltd provides practical experience translating research into medical devices, ensuring the tool can move from concept to clinically useful product. The £1.2 million fund from NIHR supports development, validation, and early clinical testing, reflecting a strong commitment to translational research that benefits patients directly.
Next Steps and Timelines
Initial phases focus on data collection, software refinement, and safety testing. The researchers plan collaborative trials across multiple paediatric clinics to evaluate performance, reliability, and user acceptance among clinicians. If successful, the tool could reach pilot deployments within a few years, subject to regulatory approvals and ongoing evaluation.
Implications for the Future of Paediatric Care
Beyond hip stability, the project demonstrates how AI can augment paediatric orthopaedics by providing evidence-based insights without replacing clinical judgment. The ultimate goal is a practical, scalable solution that supports early intervention and personalised care plans for children with cerebral palsy, helping them maintain mobility and participate more fully in daily life.
