Healthcare (Commonwealth Union) – As the artificial intelligence (AI) continues to advance, its implementation in the health care sector across the world continues to be an area of exploration. Many countries have already implemented AI to a smaller extent which assists rather than replaces existing medical staff.
The University of Glasgow in Scotland, will have a central role in a new research project investigating how AI can help detect lung cancer at an earlier stage and enhance patient safety.
The SWIFT-Lung study will evaluate a digital platform developed to assist clinicians in identifying and evaluating patients with lung nodules more efficiently and with greater accuracy. Lung cancer is the leading cause of cancer-related deaths in the UK, and improving early detection is crucial for increasing survival rates.
The project aims to show the benefits of AI-supported triage within routine National Health Service (NHS) services, with a focus on speeding up lung cancer diagnosis, reducing waiting times, and improving patient outcomes overall.
The initiative is a collaboration between 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 UK health technology firm Optellum.
At the heart of the study is the Optellum Virtual Nodule Clinic, an AI-driven platform created to help detect lung cancer earlier and improve the management of lung nodules.
A major feature of the system is its Patient Safety Net AI, which automatically scans CT reports to identify patients with lung nodules and ensures they are flagged for clinical follow-up. This reduces the risk of patients being overlooked or lost within the healthcare system, making sure those who need further assessment are quickly identified and monitored through their care journey.
Also, the platform has an AI-based Lung Cancer Prediction (LCP) model. The tool generates a personal risk score indicating the risk of a lung nodule being cancerous, enabling clinicians to prioritise patients for urgent investigation.
Together, these tools are designed to reduce diagnostic delays and at the same time reduce unnecessary tests for patients who have no signs of cancer on their tests. The platform will be embedded into existing lung cancer and lung nodule pathways of care within NHS Greater Glasgow and Clyde as part of the study.
The system aims to improve patient safety, reduce anxiety, support clinicians in making better-informed decisions and improve the efficiency of care delivery by automatically identifying potentially suspicious findings and ensuring patients are consistently followed up.
SWIFT-Lung study Chief Investigator and NHS Greater Glasgow and Clyde Consultant Radiologist Dr Mark Hall said that pulmonary nodules are frequently detected on CT scans, but guaranteeing timely and appropriate follow-up for every patient continues to be a significant challenge in healthcare. He added that SWIFT-Lung seeks to address this issue by using AI to identify, assess risk, and track patients through a structured clinical pathway.
Dr Hall pointed out that it is about providing radiology and lung cancer teams enhanced tools to tackle complex information, lower variation, and enhance patient safety with no replacement of clinical judgement or radiologists.
Dr John MacLay, Lung Cancer Lead at Glasgow Royal Infirmary and Clinical Lead for SWIFT-Lung, indicated that they are hopeful that SWIFT-Lung gives the practical value of Optellum Virtual Nodule Clinic, by ensuring each pulmonary nodule found on CT scans is correctly reviewed and followed up with appropriate care.
“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.”
Professor David Lowe who is the Director of Clinical Innovation at the University of Glasgow and Lead of the HealthTech Innovation & Translation Lab, pointed out that eventhough we have advances in imaging and pathway design, a substantial amount of lung cancers in the UK are identified at a late stage.
