A research team at Seoul National University Bundang Hospital has developed an artificial intelligence (AI) model that can diagnose sleep apnea by analyzing head and neck X-ray images.
The study was published in the Journal of Clinical Sleep Medicine.
Currently, if sleep apnea is suspected, hospitals utilize a screening test to confirm symptoms. Based on the screening test results, additional diagnostic polysomnograms may be conducted to provide a further diagnosis. Although several screening tests have been developed, they have their limitations. For instance, some have low accuracy rates, while others are not suitable for use in multi-person settings.
In response to these limitations, the research team developed a deep learning-based AI model that is capable of predicting sleep apnea by analyzing head and neck X-ray images. The AI model analyzes X-ray images of the patients’ heads and necks, with a focus on the upper airway, specifically the tongue and its surrounding structures, which are highly associated with sleep apnea. It can distinguish minute differences that are difficult to identify with the naked eye and classify the presence of sleep apnea accordingly.
The research team created the algorithm by utilizing AI training and validation, which involved using head and neck X-ray image data of 5,591 patients who visited Seoul National University Bundang Hospital. They evaluated the algorithm’s performance through internal and external testing procedures.
The results of the testing revealed that the AI model is highly accurate, with an area under the receiver operating characteristics curve of 0.82.
The research team highlighted that the head and neck X-ray imaging test required for the diagnosis of sleep apnea has the advantage of being a relatively simple and inexpensive procedure. This finding is significant as it can contribute significantly to improving the diagnosis and treatment rate of sleep apnea, which is crucial for early treatment.
“The prevalence of sleep apnea is estimated to be around 1 billion adults aged 30-69 worldwide, and the number is growing,” says Yun Chang-ho, MD, PhD, of the department of neurology, in a release. “Early detection and treatment of sleep apnea can prevent further worsening of symptoms and improve quality of life.”
With its accuracy and affordability, the team expects the model to play a major role in the early diagnosis and treatment of sleep apnea.