Published 11 Jun 2024

Optimising the Lung Cancer Pathway with AI

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Lung cancer is the UK's leading cause of cancer-related deaths, claiming nearly 35,000 lives annually. Early detection is crucial, as over 90% of patients can survive if treatment starts at stage 1. Integrating AI into the UK health system holds the promise of redesigning #LungCancer pathways, enhancing early detection, and supporting clinicians in decision-making. 
Listen to the webinar where Surabhi Srivastava, Commercial VP UK at Qure.ai, discusses AI innovations with leading UK experts: 
- Professor David Lowe, Professor of Health Innovation at the University of Glasgow and Emergency Consultant at NHS Greater Glasgow and Clyde. 
- Dr. Rhidian Bramley, Consultant Radiologist & Clinical Lead for Diagnostics, Digital, and Innovation at Greater Manchester Cancer Alliance. 
- Dr. Nick Woznitza MBE, Consultant Radiographer at UCLH and Clinical Academic at Canterbury Christ Church University. 
Professor David Lowe highlighted that a significant challenge in implementing AI is understanding the clinical pathway where the technology will be used and engaging with all stakeholders potentially affected. In Glasgow, X-rays are requested for various reasons. The team chose to focus on the outpatient pathway, primarily through primary care. By integrating appropriate technology with the optimal clinical pathway, they expedited the process for individuals flagged on X-rays to receive CT scans more quickly. 
Dr. Nick Woznitza discussed the national optimal lung cancer pathway and how a 12-month randomized trial conducted with Prof David Baldwin reduced diagnosis time from 63 to 32 days. The AI system produces a secondary image for each chest X-ray, highlighting certain abnormalities. If the AI detects a problem, it flags the X-ray for immediate review. 
Dr. Rhidian Bramley explained that in Manchester, with a population the size of Wales, they focused on patients from symptomatic pathways where chest X-rays were the first investigation. They examined the incidence of lung cancer from different referral sources. AI solutions read chest X-rays within a minute, prioritizing critical cases at the top of the list for prompt reporting. 

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