Edinburgh Researchers Test AI Method to Spot Lung Cancer Gene Changes

Scientists at the University of Edinburgh working with NHS Lothian have developed a technique that uses fluorescence lifetime imaging microscopy and artificial intelligence to detect EGFR mutations in lung cancer tissue, GB News reported. The method identifies the two most prevalent EGFR variants and showed high precision during trials.

Lung cancer remains the leading cause of cancer deaths worldwide, according to the University of Edinburgh.

Current genetic tests rely on gene sequencing that is expensive, time-consuming and consumes limited tissue from small biopsy samples. An increasing number of patients diagnosed at earlier stages has added to the volume of specimens requiring analysis. The FLIM platform captures natural light emissions from tissue and applies artificial intelligence to the resulting patterns.

GB News reported that the technique can differentiate variants critical for treatment planning. "This approach has the potential to take processes that currently cost thousands of pounds and require weeks of lab work and reduce them to something that takes minutes and costs hundreds," Dr Qiang Wang, co-lead of the study from the Institute for Regeneration and Repair, said.

"Technologies like this, which can deliver more information from smaller tissue samples at speed, will be essential for developing clinically effective diagnostic pathways," Dr David Dorward, consultant thoracic pathologist at NHS Lothian, said.

Professor Ahsan Akram, who co-led the research, said a single non-destructive scan could inform clinicians whether a patient has cancer, the type and whether it is likely to respond to targeted treatment. The research team is pursuing clinical validation and plans to extend the platform to additional cancer types and other targetable mutations while integrating the system into routine clinical practice.