A new case series shows the technology can flag suspicious nodules on images ordered for unrelated conditions, potentially expanding early detection opportunities.
A new clinical case study shows that artificial intelligence (AI) can detect potentially malignant pulmonary nodules on routine chest X-rays, even when the imaging was ordered for non-respiratory conditions. The findings, from a collaboration between Qure.ai and Hacettepe University, were presented at the IASLC World Conference on Lung Cancer 2025 in Barcelona.
The study adds to evidence that AI can serve as an early warning system in settings without formal lung cancer screening programs or complement existing CT-based screening by identifying at-risk individuals outside of typical smoker cohorts. According to the research, by increasing the number of early-detected lung cancers, survival rates can be improved through timely surgical or pharmaceutical interventions.
“By finding high-risk nodules earlier and diagnose lung cancer at early stages, AI not only improves, but also accelerates diagnosis and treatment,” says Dr Deniz Koksal at Hacettepe University in Ankara, Turkey, in a release. “This enables early surgical interventions while reducing the need for more expensive treatments such as targeted therapies and immunotherapies.”
AI as a Safety Net in Clinical Workflow
The case series, titled “Chest X-Ray Analysis with Artificial Intelligence Software Aids in the Early Diagnosis of Lung Cancer,” utilized data from the five-country CREATE study. It highlighted three cases where the AI software flagged suspicious nodules in patients who had no prior suspicion of lung cancer. The patients had undergone chest X-rays for unrelated reasons, including an emergency room visit for fever, a routine scan prior to treatment for ulcerative colitis, and an X-ray as part of a smoking cessation program.
In each instance, the AI-powered finding prompted a timely referral for CT imaging and biopsy, which confirmed early-stage lung cancer. All three patients subsequently underwent curative surgical intervention with favorable outcomes. For health systems, the technology can act as a safety net in high-volume or resource-limited settings by helping to reduce diagnostic delays.
“This new evidence presented at the World Conference of Lung Cancer has the potential to position every chest X-ray as a chance to save a life,” says Prashant Warier, Founder and CEO of Qure.ai, in a release. “AI can help to expand the early lung cancer detection funnel by identifying high-risk pulmonary nodules that would otherwise go unnoticed until it’s too late.”
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