Using AI to detect lung cancer from chest x-rays
RADICAL: A Mixed Methods Study to Assess the Clinical Effectiveness and Acceptability of an Artificial Intelligence Software to Prioritise Chest X-ray (CXR) Interpretation
This study is testing if an AI tool can help doctors find lung cancer earlier by analyzing chest x-rays to spot signs of the disease.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 60000 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | NHS Greater Glasgow and Clyde Academic / other |
| Locations | 4 sites (Glasgow and 3 other locations) |
| Trial ID | NCT06044454 on ClinicalTrials.gov |
What this trial studies
This project aims to improve the early detection of lung cancer by utilizing the qXR software, which analyzes chest x-rays with artificial intelligence to identify potential cancer features. Conducted across three sectors within NHS Greater Glasgow and Clyde, the study will assess the clinical effectiveness of qXR in prioritizing patients suspected of having lung cancer. The study includes both a clinical effectiveness evaluation and a technical retrospective analysis of chest x-ray images, along with an economic evaluation comparing costs and outcomes. Additionally, qualitative evaluations will gather insights from staff and patients regarding the acceptability of the AI tool.
Who should consider this trial
Good fit: Ideal candidates include unconsented patients aged 18 and older who have undergone a frontal chest radiograph through outpatient referrals.
Not a fit: Patients who have opted out of AI use in their clinical care or have requested removal from the study will not benefit.
Why it matters
Potential benefit: If successful, this approach could lead to earlier diagnosis and treatment of lung cancer, significantly improving patient survival rates.
How similar studies have performed: Other studies utilizing AI for radiographic analysis have shown promising results, indicating potential for success in this novel application.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Unconsented patients ≧ 18 years old with frontal chest radiograph, acquired consecutively during usual care through the outpatient (including GP) referral pathway only, whose radiograph has not already been reported (applies to clinical effectiveness and health economic evaluation studies). * Unconsented patients ≧ 18 years old with frontal chest radiograph, sampled from images already acquired and reported in the current or previous calendar year (applies to technical evaluation). * Key stakeholders such as NHS service users, healthcare staff and NHS management (applies to qualitative evaluation). Exclusion Criteria: * Patient has requested that they are removed from the study, or has objected to the use of AI in their routine clinical care and this has been subsequently upheld by the health board (applies to clinical effectiveness study, health economic evaluation and technical evaluation).
Where this trial is running
Glasgow and 3 other locations
- Glasgow Royal Infirmary (North Sector) — Glasgow, United Kingdom (Recruiting)
- NHS Greater Glasgow and Clyde — Glasgow, United Kingdom (Enrolling_by_invitation)
- Queen Elizabeth University Hosp (South Sector) — Glasgow, United Kingdom (Not_yet_recruiting)
- The Royal Alexandra Hospital (Clyde Sector) — Paisley, United Kingdom (Recruiting)
Study contacts
- Principal investigator: David Lowe — NHS Greater Glasgow and Clyde Board HQ
- Study coordinator: Ruairidh Davison
- Email: ruairidh.davison@ggc.scot.nhs.uk
- Phone: 0141 451 6869
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.