Could people be screened passively for early detection and prevention of osteoporosis via an automated review of their existing imaging test results and medical records?
That is the aim of a collaboration between Israeli AI startup Zebra Medical Vision and Scottish digital transformation consultancy Storm ID.
Osteoporosis, a condition causing weak and brittle bones, is a major public health concern. Fragility fractures — not related to high-impact trauma — are the major complication of this underdiagnosed and undertreated condition, especially for the aging population.
The two entities won a UK-Israel research and development competition with their proposal for a machine learning/artificial intelligence system that can identify people at risk of fractures by analysis of medical imaging data such as CTs, plus information in patient records.
An international, multidisciplinary team of clinicians, data scientists and computer scientists will work together for two years, based at NHS Greater Glasgow and Clyde (Scotland) and Assuta Medical Centers (Israel).
Dr. Michal Guindy, head of imaging and innovation at Assuta, noted that more than 200,000 CTs are done at Assuta hospitals annually. “It is exciting to think that we can play a significant role in early detection of osteoporosis. By analyzing studies that were done for other clinical indications, we can help prevent fractures and contribute to solving a public health challenge of growing concern.”
The project is co-funded in part by the two countries under the EUREKA framework to foster industrial research collaboration between the UK and Israel.
Storm ID Director Paul McGinness said: “By predicting ahead of time the potential risk of bone fracture, we can intervene earlier to treat and manage the risk, which is better for the patient and for the health system.”