NHS Greater Glasgow & Clyde is to play a leading role in a new UK study exploring how AI could be used to support earlier lung cancer diagnosis and improve patient safety.
Researchers will test a new digital platform designed to help clinicians identify and assess patients with lung nodules more quickly and accurately.
While the vast majority of nodules are harmless, doctors must evaluate them carefully because early-stage lung cancer initially presents as a nodule.
The aim of the ‘Swift-Lung’ study is to demonstrate the impact of AI-enabled triage in routine NHS care focusing on earlier lung cancer diagnosis, reduced waiting times, and ultimately improved outcomes for patients.
Dr Mark Hall, consultant radiologist at NHS Greater Glasgow and Clyde 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.”
Swift-Lung will be conducted as a prospective, ‘stepped-wedge’ clinical trial across multiple NHS sites in England and Scotland, including NHS Greater Glasgow and Clyde, NHS Highland, and Oxford University Hospitals.
It will also involve the West of Scotland Innovation Hub and the University of Glasgow’s HealthTech Innovation and Translation Lab. Health technology company Optellum has been awarded funding from the National Institute for Health and Care Research (NIHR) after a competitive process.
At the centre of the study is the Optellum ‘virtual nodule clinic’, an AI-enabled system designed specifically to support earlier lung cancer diagnosis and improve how lung nodules are managed.
A key element of the platform is its ‘patient safety net AI’, which automatically highlights patients with lung nodules from CT scan reports, for clinical follow-up.
This means no patient is missed or lost in the system, helping to ensure that those who may need further investigation or follow up are flagged promptly and tracked through their care pathway.
Alongside this, the system uses an AI‑powered ‘lung cancer prediction’ (LCP) model. This model calculates a personalised risk score to assess the likelihood that a lung nodule could be cancerous, supporting clinicians to prioritise those at highest risk for urgent follow-up.
Together, these tools aim to reduce delays in diagnosis, while avoiding unnecessary investigations for patients with non-cancerous findings.
Within NHS Greater Glasgow and Clyde, the platform will be integrated into existing lung cancer and lung nodule pathways as part of the study.
By automatically flagging potentially concerning findings and ensuring consistent follow-up, the approach is designed to improve patient safety and reduce anxiety, while also supporting clinical decision-making and streamlining care.
Swift-Lung stands for ‘streamlined workflow for investigation and fast-tracking lung cancer diagnosis’ and will be conducted over three years.
Dr Johnathan Watkins, PhD, Optellum’s CEO, 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.”
