An x-ray machine operator stands next to a protective lead shield which has a little window for viewing the patient. The electro-therapeutic guide. 1912.
A new non-invasive imaging technique called raster-scan optoacoustic mesoscopy (RSOM) shows promise for detecting diabetes progression and severity by visualizing microscopic changes in the skin’s blood vessels. Recently published research from the Technical University of Munich (TUM) and Helmholtz Munich reveals RSOM’s ability to create detailed three-dimensional maps of the skin’s microvasculature down to capillary dimensions. Machine learning then pinpoints subtle alterations reflecting vascular damage tied to advancing diabetes.
Tracking disease progression in diabetes remains a major challenge. Current blood tests like glycated hemoglobin (HbA1c) analysis lack sensitivity for detecting early vascular complications or monitoring subtle worsening over time. Skin manifestations also tend to appear late and crudely indicate systemic microvascular damage. This often delays interventions until irreversible organ injury sets in.
The new technique leverages the skin’s accessibility to “read out” diabetes’ impacts on tiny vessels in ways not previously possible. It images living tissue without dyes or contrast agents using optical and ultrasonic waves. Powerful AI methods then extract and analyze hundreds of explainable microvascular features predictive of diabetes severity.
High-resolution images of terminals in water chains.
Shiotari, A., Sugimoto, Y. Ultrahigh-resolution imaging of water networks by atomic force microscopy. Nat Commun 8, 14313 (2017). https://doi.org/10.1038/ncomms14313
A new system that allows trans-scale optical imaging of large field of view and volume so that cells in whole organs and tissues can be mapped dynamically
Read the published research article here
Video from work by Taro Ichimura and colleagues
Transdimensional Life Imaging Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan
Video originally published with a Creative Commons Attribution 4.0 International (CC BY 4.0)
Published in bioRxiv, February 2024 (not peer reviewed)
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