Nanox Announces AI Software Increases Identification of Patients with Vertebral Compression Fractures, an early sign of Osteoporosis, Up to Six-Fold

– According to early findings in the ADOPT study, Nanox.AI software improves detection of key risk factor for osteoporosis, outperforming UK National Health Service national average

– Findings demonstrate real-world impact of integrating AI technology in routine chest and abdomen CT scans to improve detection of spine fracture, an early sign of osteoporosis

PETACH TIKVA, Israel, March 12, 2024 (GLOBE NEWSWIRE) -- NANO-X IMAGING LTD ("Nanox" or the "Company," Nasdaq: NNOX), an innovative medical imaging technology company, and its deep-learning medical imaging analytics subsidiary, Nanox AI Ltd. (Nanox.AI), today announced that early findings from the AI-enabled Detection of OsteoPorosis for Treatment (ADOPT) study, which uses a Nanox.AI artificial intelligence solution, HealthVCF, to review routine CT scans, have identified up to six times more patients with vertebral compression fracture than the national average at National Health Services (NHS) hospitals in the UK, which include University of Oxford and other healthcare centers.

Results from the NHS Falls and Fragility Fracture Audit Programme (FFFAP) show that across ADOPT sites, such as the University Hospital Southampton NHS Foundation Trust, where the HealthVCF bone solution has been deployed, there has been a substantial increase in the rate of patient identification based on spine fractures, surpassing the national average with a remarkable up to sixfold increase in the number of patients identified and included for follow-up in the Fracture Liaison Service (FLS) database.

Thus far in the study, the Nanox.AI algorithm has identified over 2,400 patients with VCF from routine CT scans that were not known to the NHS’s hospitals, and have since been flagged for follow-up assessments. The study will continue through February 2025.

“My colleagues and I are encouraged by these findings, which show the potential of an AI-directed pathway for identifying vertebral compression fractures in patients who can then be checked for osteoporosis and start treatments that significantly reduce their fracture risk with benefits to the patient, their family, healthcare system and wider society,” said Professor Kassim Javaid, who is leading the research at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford. “Leveraging AI-powered population health solutions presents an effective and efficient avenue for early identification of patients at very high risk of fractures, facilitating timely intervention and care. Proactively identifying and intervening in potential health risks not only preserves well-being but also contributes to significant cost savings and return on investment for the healthcare system.”