Nanox.AI, a subsidiary of Israeli medical imaging innovator Nanox, has achieved a significant milestone with its AI-powered bone assessment software, HealthOST and HealthVCF, receiving recommendation from the UK’s National Institute for Health and Care Excellence (NICE). This endorsement permits the use of these advanced AI solutions within National Health Service (NHS) hospitals across the UK for a three-year Early Value Assessment period. During this time, their effectiveness in detecting vertebral fragility fractures (VFFs) will be closely evaluated alongside current NHS diagnostic practices.

These AI tools leverage deep learning to analyse routine CT scans, often conducted for unrelated medical reasons, enabling opportunistic detection of subtle fractures that may otherwise be overlooked. Importantly, this method involves no additional scanning, radiation exposure, or patient burden, offering a cost-effective pathway to earlier identification of individuals at risk of osteoporosis and subsequent fractures. HealthOST represents an evolution of the initially trialed HealthVCF solution, which was previously evaluated in the AI-enabled Detection of OsteoPorosis (ADOPT) study led by the University of Oxford.

Professor Kassim Javaid, a leading expert in osteoporosis and bone disease from Oxford University, hailed the endorsement as a major advance in osteoporosis care. He highlighted that integrating AI into routine NHS workflows could transform the early detection and intervention landscape, potentially improving patient outcomes by preventing more severe fractures and reducing the associated long-term disability, pain, and loss of independence. The ADOPT study demonstrated the clinical impact of such proactive identification, and Oxford’s ongoing collaboration signals a commitment to building robust evidence supporting these technologies.

NICE’s Health Technology Evaluation emphasises that AI solutions like HealthOST and HealthVCF support clinicians in identifying vertebral fractures opportunistically when scans are performed for unrelated indications. This identification is crucial because many fragility fractures remain undiagnosed, leaving patients vulnerable to further injury. The AI tools are integrated with existing Picture Archiving and Communication Systems (PACS), providing real-time, actionable clinical insights without disrupting established workflows.

Beyond Nanox's offerings, NICE has recommended five AI technologies in total for this evidence generation period, including BriefCase-Triage, CINA-VCF Quantix, and IB Lab FLAMINGO, all intended to aid the NHS in advancing osteoporosis fracture detection. These technologies must meet regulatory requirements, including NHS England’s Digital Technology Assessment Criteria, to ensure compliance and patient safety. The evidence generation plan outlined by NICE demands rigorous data collection to address current knowledge gaps, focusing on real-world clinical effectiveness and comparative outcomes versus standard care.

Nanox’s CEO, Erez Meltzer, viewed the NICE recommendation as a significant validation of Nanox.AI’s clinically proven, real-world results, distinguishing the company’s solutions amid a competitive landscape where many purported AI offerings lack evidence of tangible clinical benefits. By securing core NHS funding eligibility, Nanox positions itself to deepen its footprint within UK healthcare settings, working collaboratively with the NHS to demonstrate improved detection and diagnosis of bone diseases through AI.

The broader Nanox ecosystem aims to revolutionise medical imaging by combining affordable, AI-enhanced digital X-ray technology with cloud-based analysis and remote expert support. This reflects the company's vision of expanding access to preventive health care worldwide, improving early detection and treatment pathways through technological innovation.

In summary, the inclusion of Nanox.AI’s HealthOST and HealthVCF in NICE’s Early Value Assessment represents a noteworthy development in the adoption of artificial intelligence in clinical diagnostics. It underscores the growing recognition of AI’s potential to enhance osteoporosis care by identifying high-risk patients earlier and enabling timely, preventive interventions within the NHS framework.

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Source: Noah Wire Services