NHS Greater Glasgow and Clyde is leading a new study focused on improving lung cancer diagnosis and patient safety.
The SWIFT-Lung study will test a digital platform that uses AI to help doctors identify and assess patients with lung nodules more quickly and accurately.
The study will involve NHS Greater Glasgow and Clyde, the West of Scotland Innovation Hub, the University of Glasgow’s HealthTech Innovation and Translation Lab, NHS Highland, Oxford University Hospitals NHS Foundation Trust and health technology company Optellum.
Central to the study is the Optellum Virtual Nodule Clinic, an AI-powered system designed to improve the management of lung nodules.
One of its key features is the Patient Safety Net AI, which automatically flags patients with lung nodules identified in CT scan reports, ensuring timely clinical follow-up.
The system also includes a Lung Cancer Prediction model, which calculates a personalised risk score to estimate the likelihood that a nodule could be cancerous.
This helps clinicians prioritise high-risk patients for urgent follow-up while avoiding unnecessary investigations for those with non-cancerous nodules.
Within NHS Greater Glasgow and Clyde, the Optellum platform will be integrated into existing lung cancer and nodule pathways as part of the study.
Dr John MacLay, lung cancer lead at Glasgow Royal Infirmary and clinical lead for SWIFT-Lung, said: "We hope that SWIFT-Lung will demonstrate the real-life utility of Optellum's Virtual Nodule Clinic, ensuring all pulmonary nodules identified and reported on CT scans are reviewed and appropriate follow up is implemented.
"This AI-driven solution has the potential to reduce the clinical risk of missed nodules that may represent early lung cancers and accelerate the diagnostic pathway to allow early curative intervention."
Dr Mark Hall, consultant radiologist and chief investigator for SWIFT-Lung, said: "Pulmonary nodules are commonly identified on CT scans, but ensuring every patient receives the right follow-up at the right time remains a major challenge across healthcare systems.
"SWIFT-Lung aims to close that gap by using AI to help identify, risk assess and track patients through a structured pathway.
"This is about giving radiology and lung cancer teams better tools to manage complex information, reduce variation, and improve patient safety.
"Not replacing clinical judgement or radiologists."
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Professor David Lowe, director of clinical innovation at the University of Glasgow and lead of the HealthTech Innovation and Translation Lab, said: "Despite advances in imaging and pathway design, a substantial proportion of lung cancers in the UK are still diagnosed at a late stage.
"SWIFT-Lung addresses this by generating robust, real-world evidence on whether AI-enabled triage approaches – such as Optellum’s Virtual Nodule Clinic – can be safely and effectively integrated into routine practice to support earlier identification of high-risk nodules.
"This is about helping clinical teams to ensure that actionable findings are identified promptly and not missed, ultimately improving outcomes for patients."
The study aims to reduce delays in diagnosis, improve patient safety, and support clinical decision-making through a more consistent, structured approach.
Optellum’s CEO, Dr Johnathan Watkins, said: "Optellum is honoured to have been selected and trusted for the SWIFT-Lung project to help NHS teams improve lung cancer care pathways.
"This project shows how committed we are to supporting health systems with responsible, evidence-based innovations that have real-world impact for patients and providers.
"Most importantly, we want to help patients get the timely care they need and potentially reduce the uncertainty that often comes with receiving a lung cancer diagnosis."
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