AI Technology Improves Identification of Osteoporosis

UCB will license its Artificial Intelligence (AI)-based fracture identification technology, BoneBot, to ImageBiopsy Lab to bring the new identification tool to clinical practice by 2023. The radiology AI solution will screen CT scans to detect the presence of “silent” or asymptomatic fractures in the spine which can otherwise go unrecognized and unreported.

ImageBiopsy Lab will integrate UCB's BoneBot technology with its existing ImageBiopsy Lab ZOO MSK platform for delivery to hospitals to help to increase the reporting of spinal fractures, enabling diagnosis and treatment earlier in the treatment journey, potentially reducing the co-morbidities associated with osteoporosis.

“As digitalization of health increases, so does the potential of leveraging AI for improving care for many diseases, including osteoporosis. The number one risk factor for fragility fractures is a previous fracture. Identifying and appropriately treating patients who have already suffered a vertebral fracture is therefore key to ensuring that patients can continue to live their life to the fullest and avoid further fracture,” said Emmanuel Caeymaex, Executive Vice President Immunology Solutions & Head of US at UCB. “Together with expert clinicians, UCB has developed a deep-learning computational model that can detect vertebral compression fractures on CT scans. Partnering with a leading musculoskeletal (MSK) radiology AI company will ensure this technology can be integrated into clinical care.

“It is our ambition to support the more than 9 million patients worldwide who suffer a fragility fracture due to osteoporosis each year by helping to identify those patients at highest risk. Strategic partnerships and investment with those who have the technology and data capabilities can drive our transformation further in the most impactful ways. We're delighted to be working with ImageBiopsy Lab to launch this important technology,” he said.

Currently, more than two-thirds of vertebral fractures are undiagnosed. Identifying them systematically has proven to be challenging for all clinicians.

“The under-reporting in CT scans and consequent under-treating of vertebral fractures remains a real challenge in health systems across the world but this can be improved by a standard classification and a clearer path of care,” said Bo Abrahamsen, Endocrinologist and Professor of Musculoskeletal Epidemiology. “Although CT scans done for other purposes have the potential to identify vertebral fractures, scans containing vertebral fractures are often not assessed with this in mind, given the high time pressures on radiologists. There has to be a fast, simple, and intuitive way for vertebral fractures to be detected and brought to the attention of the services responsible for osteoporosis assessments. At the moment, these fractures are hiding in plain sight. We welcome digital innovation which can enable us to deliver clinical intervention earlier, ensuring patients receive the care they need.”