AI-Powered chest X-Rays detect lung cancer early

New evidence highlights AI’s potential in early lung cancer detection

At the IASLC 2024 World Conference on Lung Cancer in San Diego, a new study has demonstrated that AI-powered chest X-ray interpretation can identify lung nodules that may develop into early-stage lung cancers nearly three years before symptoms appear.

The study, conducted at Phrapokklao Hospital’s Cancer Centre of Excellence in Bangkok, Thailand, showed an average diagnostic delay of nearly three years from the first abnormal chest X-ray. Led by Dr. Passakorn Wanchaijiraboon, Medical Oncologist and Deputy Director, the research utilised the Qure.ai chest X-ray AI solution, qXR.

Dr Passakorn Wanchaijiraboon explained: “This abstract study, presented at the World Conference on Lung Cancer, provides a snapshot of the significant potential that AI-assisted chest X-ray analysis holds for transforming early cancer detection and reducing the rate of missed lung cancer diagnoses.

“In most Thai government hospitals, chest X-rays are interpreted by non-radiologists. However, in community hospitals, there are often no radiologists available to read chest X-rays at all. By overlaying specialist AI to read all cases, we can support clinicians in detecting incidental high-risk nodules that may lead to lung cancer. This approach can streamline decision-making and potentially improve patient survival through the earlier diagnosis of cancer.”

The study reviewed chest X-ray images of newly diagnosed lung cancer patients over a year, finding that 18% of cases had a missed lung cancer diagnosis over an average period of nearly three years. Half of these cases were incidentally detected during health check-ups for non-respiratory symptoms.

“This is an exciting evidence example that underscores the transformative potential of AI in the fight against lung cancer,” said Bhargava Reddy, Chief Business Officer at Oncology at Qure.ai. “Overlaying AI on chest X-rays casts the net wider by proactively triaging patients for the risk of lung cancer, detecting cancers earlier in currently invisible and unprofiled patient populations.”

Lung cancer remains one of the deadliest cancers, with over two-thirds of patients diagnosed at an advanced stage when curative treatment is no longer feasible.

Missed lung cancer diagnoses are a significant concern for clinicians and a major medicolegal challenge, with missed nodules being the third most common reason for malpractice claims.