Skin Complications of Diabetes Mellitus Revealed by Polarized Hyperspectral Imaging and Machine Learning
Top Cited Papers
Open Access
- 6 January 2021
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 40 (4), 1207-1216
- https://doi.org/10.1109/tmi.2021.3049591
Abstract
Aging and diabetes lead to protein glycation and cause dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. In fact, no methods of non-invasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, currently exist for endocrinologists and clinical diagnosis. In this publication, utilizing emerging photonics-based technology, innovative solutions in machine learning, and definitive physiological characteristics, we introduce a diagnostic approach capable of evaluating the skin complications of diabetes mellitus at the very earlier stage. The results of the feasibility studies, as well as the actual tests on patients with diabetes and healthy volunteers, clearly show the ability of the approach to differentiate diabetic and control groups. Furthermore, the developed in-house polarization-based hyperspectral imaging technique accomplished with the implementation of the artificial neural network provides new horizons in the study and diagnosis of age-related diseases.Funding Information
- Academy of Finland (314369 (RADDESS program), 290596, 318281)
- INFOTECH strategic fund
- European Union’s Horizon 2020 Research and Innovation Program through the Marie Skłodowska-Curie (839888)
This publication has 58 references indexed in Scilit:
- Advanced glycation end productsDermato-Endocrinology, 2012
- Online object oriented Monte Carlo computational tool for the needs of biomedical opticsBiomedical Optics Express, 2011
- Assessing diabetic foot ulcer development risk with hyperspectral tissue oximetryJournal of Biomedical Optics, 2011
- Evaluation of Diabetic Foot Ulcer Healing With Hyperspectral Imaging of Oxyhemoglobin and DeoxyhemoglobinDiabetes Care, 2009
- The Use of Medical Hyperspectral Technology to Evaluate Microcirculatory Changes in Diabetic Foot Ulcers and to Predict Clinical OutcomesDiabetes Care, 2007
- In vivo data of epidermal thickness evaluated by optical coherence tomography: Effects of age, gender, skin type, and anatomic siteJournal of Dermatological Science, 2006
- Polarized light propagation through scattering media: time-resolved Monte Carlo simulations and experimentsJournal of Biomedical Optics, 2003
- Viscoelastic properties of collagen: synchrotron radiation investigations and structural modelPhilosophical Transactions B, 2002
- Imaging skin pathology with polarized lightJournal of Biomedical Optics, 2002
- The influence of age and sex on skin thickness, skin collagen and densityBritish Journal of Dermatology, 1975