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Noninvasive detection of diabetes mellitus based on skin fluorescence and diffuse reflectance spectroscopy.

Authors :
Zhang, Yuanzhi
Liu, Yong
Zhu, Guoqing
Wang, Quanfu
Ni, Jingshu
Liu, Lin
Zhang, Jian
Zhang, Junqing
Li, Zhongsheng
Wang, Xia
Huang, Yao
Dong, Meili
Zhang, Yang
Wang, Yikun
Source :
Journal of Biophotonics; Jan2024, Vol. 17 Issue 1, p1-14, 14p
Publication Year :
2024

Abstract

There is an urgent need for a mass population screening tool for diabetes. Skin tissue contains a large number of endogenous fluorophores and physiological parameter markers related to diabetes. We built an excitation‐emission spectrum measurement system with the excited light sources of 365, 395, 415, 430, and 455 nm to extract skin characteristics. The modeling experiment was carried out to design and verify the accuracy of the recovery of tissue intrinsic discrete three‐dimensional fluorescence spectrum. Blood oxygen modeling experiment results indicated the accuracy of the physiological parameter extraction algorithm based on the diffuse reflectance spectrum. A community population cohort study was carried out. The tissue‐reduced scattering coefficient and scattering power of the diabetes were significantly higher than normal control groups. The Gaussian multi‐peak fitting was performed on each excitation‐emission spectrum of the subject. A total of 63 fluorescence features containing information such as Gaussian spectral curve intensity, central wavelength position, and variance were obtained from each person. Logistic regression was used to construct the diabetes screening model. The results showed that the area under the receiver operating characteristic curve of the model for predicting diabetes was 0.816, indicating a high diagnostic value. As a rapid and non‐invasive detection method, it is expected to have high clinical value. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1864063X
Volume :
17
Issue :
1
Database :
Complementary Index
Journal :
Journal of Biophotonics
Publication Type :
Academic Journal
Accession number :
174934550
Full Text :
https://doi.org/10.1002/jbio.202300098