Check out these RSOM images of the skin of a healthy volunteer (left) and a patient with diabetes. They are really fascinating! Credit: Technical University Munich
Researchers at the Technical University of Munich (TUM) and Helmholtz Munich are using artificial intelligence (AI) and high-resolution optoacoustic imaging technology to measure microvascular changes in the skin and assess the severity of diabetes. Find out more about their groundbreaking work published in the journal Nature Biomedical Engineering.
Using light pulses to generate ultrasound inside tissue, optoacoustic imaging methods capture detailed images of blood vessels in ways not possible by other non-invasive techniques. This is a big step forward for medical applications and a potential game-changer in the treatment of diabetes.
The team of researchers led by Professor Vasilis Ntziachristos has developed innovative optoacoustic imaging methods, including RSOM, to study the effects of diabetes on the human skin. They have successfully identified characteristics of diabetes using RSOM images and an AI algorithm, revealing 32 significant changes based on alterations of the skin microvasculature appearance, such as the number of branches of the vessels or their diameter.
RSOM measurements are non-invasive and quick, making it ideal for evaluating vascular changes in diabetes. They provide valuable data on different depths of the skin simultaneously, uncovering how diabetes affects vessels at different skin layers differently. This depth of detail is unmatched by other optical imaging methods and has the potential to transform our understanding of diabetes and its impact on the body.
For more information about this incredible research and its potential implications for the treatment of diabetes, check out the full article here.
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