Funding outcome

Scoliosis is a condition where a child’s spine curves abnormally. It affects about 3% of children and is more common in girls, who are more likely to develop worsening curves. To choose the best treatment, doctors need to know how much growth a child has remaining. This is important because treatments such as bracing work best during periods of rapid growth. Another option, called vertebral body tethering, is a less invasive surgery that helps guide the spine as a child grows. Both treatments depend on precise timing. If this opportunity is missed, the curve may worsen and require more invasive surgery. Today, doctors use spine X-rays to monitor scoliosis. These images show the spinal curve and provide a rough estimate of growth. Hand X-rays can provide more detailed information, but they take time to interpret, and results may vary between doctors. Because scoliosis care often continues for several years, children may undergo many X-rays during growth. This increases cumulative radiation exposure over time. There is currently no simple, accurate, and radiation-free method to measure growth during routine scoliosis care. This project will develop a new method that uses ultrasound and artificial intelligence (computer-based image analysis) to assess growth from hand images. The system will automatically analyze ultrasound images and provide a clear, consistent measure of growth during the key stages when treatment decisions are most important. The method is designed to be fast, easy to use, and provide results immediately during clinic visits. By reducing the need for repeated X-rays, this approach could improve safety and allow more frequent monitoring. Because ultrasound devices are portable, this technology may also improve access to scoliosis care in rural and remote communities. Overall, this project aims to make scoliosis care safer, more accurate, and easier to access, while helping children receive the right treatment at the right time.