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Nano-X Imaging to present data from ADOPT study of AI bone solution

Nano-X Imaging to present data from ADOPT study of AI bone solution

NANO-X IMAGING’s (NNOX) Nanox AI will present new data from the AI-enabled Detection of OsteoPorosis for Treatment study at four major upcoming medical conferences spanning March through June 2025. The ADOPT study concluded in February 2025 and evaluated HealthVCF at four National Health Services trusts: Cambridge, Bradford, Cardiff and Southampton – coordinated by the long-standing clinical users at Oxford. In earlier findings from the ADOPT study, HealthVCF analyzed 37,220 routine medical CT scans and identified over 3,450 new patients with vertebral compression fractures, up to six times more than the national average at NHS hospitals in the UK. These patients were asymptomatic, and the early data underscores the importance of addressing the critical gap in detection of patients with vertebral fractures. Kassim Javaid, Professor of Osteoporosis and Adult Rare Bone Diseases and lead investigator of the ADOPT study, will present expanded data from the study showcasing the clinical utility of the AI bone solution in assessing bone health and identifying key indicators of osteoporosis, along with the benefits of various approaches to its implementation and the effect it can have on the rate of patient detection. The presented data will also show the economic benefit that such AI tools can bring to a healthcare organization. The ADOPT study has shown that AI-enabled Fracture Liaison Services, together with other improvements, led to a reduction in patient refracture rates of up to 10% and cost savings of up to GBP 50,000 per healthcare organization over the course of the study. A more recent version of the AI bone solution, HealthOST, is FDA-cleared and was developed by Nanox AI following the initiation of the ADOPT study. HealthOST features improved precision in measuring fractures and the new ability to highlight low bone mineral density in routine CT scans, without requiring additional imaging or radiation exposure for the patient.

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