Please use this identifier to cite or link to this item:
For citation please use:
Main Title: Development and Testing of an LED-Based Near-Infrared Sensor for Human Kidney Tumor Diagnostics
Author(s): Bogomolov, Andrey
Zabarylo, Urszula
Kirsanov, Dmitry
Belikova, Valeria
Ageev, Vladimir
Usenov, Iskander
Galyanin, Vladislav
Minet, Olaf
Sakharova, Tatiana
Danielyan, Georgy
Feliksberger, Elena
Artyushenko, Viacheslav
Type: Article
Language Code: en
Abstract: Optical spectroscopy is increasingly used for cancer diagnostics. Tumor detection feasibility in human kidney samples using mid- and near-infrared (NIR) spectroscopy, fluorescence spectroscopy, and Raman spectroscopy has been reported (Artyushenko et al., Spectral fiber sensors for cancer diagnostics in vitro. In Proceedings of the European Conference on Biomedical Optics, Munich, Germany, 21–25 June 2015). In the present work, a simplification of the NIR spectroscopic analysis for cancer diagnostics was studied. The conventional high-resolution NIR spectroscopic method of kidney tumor diagnostics was replaced by a compact optical sensing device constructively represented by a set of four light-emitting diodes (LEDs) at selected wavelengths and one detecting photodiode. Two sensor prototypes were tested using 14 in vitro clinical samples of 7 different patients. Statistical data evaluation using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) confirmed the general applicability of the LED-based sensing approach to kidney tumor detection. An additional validation of the results was performed by means of sample permutation.
Issue Date: 19-Aug-2017
Date Available: 23-Aug-2019
DDC Class: 610 Medizin und Gesundheit
530 Physik
Subject(s): tumor detection
fiber spectroscopy
optical sensor
near infrared
Journal Title: Sensors
Publisher: MDPI
Publisher Place: Basel
Volume: 17
Issue: 8
Article Number: 1914
Publisher DOI: 10.3390/s17081914
EISSN: 1424-8220
Appears in Collections:FG Nichtlineare Optik » Publications

Files in This Item:
Format: Adobe PDF | Size: 4.12 MB
DownloadShow Preview

Item Export Bar

This item is licensed under a Creative Commons License Creative Commons