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In a groundbreaking study, researchers from Tsinghua University in Beijing, China, have demonstrated that combining facial thermal imaging with artificial intelligence (AI) can accurately detect the risk of coronary artery disease (CAD). The findings, published on Tuesday in the journal BMJ Health & Care Informatics, reveal a promising new tool for the assessment and early diagnosis of this potentially fatal condition.
Coronary artery disease, caused by the buildup of plaques in the heart’s major blood vessels, can lead to severe complications such as heart attacks. Traditionally, diagnosing CAD has relied on a mix of probability assessments of risk factors, electrocardiograms (ECGs), angiograms, and blood tests. These methods, while effective, are often time-consuming, invasive, and not always accurate or widely applicable.
The research led by Tsinghua University showcases the efficacy of thermal imaging in capturing temperature distribution and variations on the skin’s surface by detecting infrared radiation emitted by the body. When coupled with AI, this technology can identify areas of abnormal blood circulation and inflammation from skin temperature patterns, offering a non-invasive and real-time diagnostic tool that surpasses conventional methods in effectiveness.
In the study, 460 individuals with suspected heart disease underwent thermal imaging of their faces. These images were then analyzed using an AI-assisted model. The results were compelling: 322 participants, or 70%, were confirmed to have coronary artery disease. This new method proved to be about 13% more effective at predicting CAD than traditional pretest risk assessments.
“The feasibility of thermal imaging-based CAD prediction suggests potential future applications and research opportunities,” the research team stated. They emphasized the technology’s ability to provide disease-relevant information that goes beyond traditional clinical measures, which could enhance the assessment of atherosclerotic cardiovascular disease and related chronic conditions.
The researchers call for larger studies to further validate and explore the potential of this biophysiological-based health assessment modality. If adopted into clinical practice, this innovative approach could revolutionize the way coronary artery disease is diagnosed and managed, providing a faster, more accurate, and non-invasive option for patients worldwide.
As the medical community continues to explore the integration of AI and advanced imaging technologies, this study marks a significant step forward in the ongoing effort to improve cardiovascular health and patient outcomes.
