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Article

Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage.

Nature biomedical engineering - 1 Dec 2023

Karlas Angelos, Katsouli Nikoletta, Fasoula Nikolina-Alexia, Bariotakis Michail, Chlis Nikolaos-Kosmas, Omar Murad, He Hailong, Iakovakis Dimitrios, Schäffer Christoph, Kallmayer Michael, Füchtenbusch Martin, Ziegler Annette, Eckstein Hans-Henning, Hadjileontiadis Leontios, Ntziachristos Vasilis

Abstract excerpt

Skin microangiopathy has been associated with diabetes. Here we show that skin-microangiopathy phenotypes in humans can be correlated with diabetes stage via morphophysiological cutaneous features extracted from raster-scan optoacoustic mesoscopy (RSOM) images of skin on the leg. We obtained 199 RSOM images from 115 participants (40 healthy and 75 with diabetes), and used machine learning to segment skin layers...

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Identifiers

PMID: 38049470
DOI: 10.1038/s41551-023-01151-w
PMCID: PMC10727986

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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