Diagnosis of Diabetes Based on Analysis of Exhaled Air by Terahertz Spectroscopy and Machine Learning

被引：12

作者：

Kistenev, Yu, V ^{[1
,2
]}

Teteneva, A., V ^{[2
]}

Sorokina, T., V ^{[2
]}

Knyazkova, A., I ^{[1
,3
]}

Zakharova, O. A. ^{[1
,3
]}

Cuisset, A. ^{[4
]}

Vaks, V. L. ^{[5
]}

Domracheva, E. G. ^{[5
]}

Chernyaeva, M. B. ^{[5
]}

Anfertev, V. A. ^{[5
]}

Sim, E. S. ^{[1
,2
]}

Yanina, I. Yu ^{[1
,6
]}

Tuchin, V. V. ^{[1
,6
,7
]}

Borisov, A., V ^{[1
,2
]}

机构：

[1] Natl Res Tomsk State Univ, Tomsk 634050, Russia

[2] Siberian State Med Univ, Tomsk 634050, Russia

[3] Russian Acad Sci, Siberian Branch, Inst Strength Phys & Mat Sci, Tomsk 634055, Russia

[4] Univ Littoral Cote dOpale, F-59140 Dunkerque, France

[5] Russian Acad Sci, Inst Phys Microstruct, Nizhnii Novgorod 603087, Russia

[6] Saratov Natl Res State Univ, Saratov 410012, Russia

[7] St Petersburg Natl Res Univ Informat Technol Mech, ITMO Univ, St Petersburg 197101, Russia

来源：

OPTICS AND SPECTROSCOPY | 2020年 / 128卷 / 06期

基金：

俄罗斯基础研究基金会;

关键词：

diabetes; expired air; terahertz spectroscopy; machine learning; OXIDATIVE STRESS; TYPE-2; MELLITUS; BIOMARKERS; MARKERS;

D O I：

10.1134/S0030400X20060090

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Results of studying the exhaled air of patients with diabetes mellitus in comparison with healthy volunteers with the use of broadband terahertz time-domain spectroscopy are presented. Typical spectral subranges in which absorption spectrum profiles of breath tests of the target and control group differ most significantly are revealed: 0.560, 0.738, 0.970, 1.070, 1.140, 1.180, and 1.400 THz. Using the principal component analysis, it is shown that the set of absorption coefficients in these regions allows one to reliably separate the target and control groups. The obtained results are compared with measurements of acetone vapors in the exhaled air of patients with diabetes mellitus and healthy volunteers.

引用

页码：809 / 814

页数：6

共 33 条

[1]

[Anonymous], 2002, PRINCIPAL COMPONENT

[2] A review of mortality in type 2 diabetes mellitus [J].

Asfandiyarova, N. S. .

DIABETES MELLITUS, 2015, 18 (04) :12-21

[3] Exhaled Molecular Fingerprinting in Diagnosis and Monitoring: Validating Volatile Promises [J].

Boots, Agnes W. ;

Bos, Lieuwe D. ;

van der Schee, Marc P. ;

van Schooten, Frederik-Jan ;

Sterk, Peter J. .

TRENDS IN MOLECULAR MEDICINE, 2015, 21 (10) :633-644

[4]

Colwell J. A., 2003, DIABETES HOT TOPICS

[5] Significance of Exhaled Breath Test in Clinical Diagnosis: A Special Focus on the Detection of Diabetes Mellitus [J].

Das, Souvik ;

Pal, Saurabh ;

Mitra, Madhuchhanda .

JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING, 2016, 36 (05) :605-624

[6] STANDARDS OF SPECIALIZED DIABETES CARE [J].

Dedov, I ;

Shestakova, M. ;

Mayorov, A. ;

Vikulova, O. ;

Galstyan, G. ;

Kuraeva, T. ;

Peterkova, V ;

Smirnova, O. ;

Starostina, E. ;

Surkova, E. ;

Sukhareva, O. ;

Tokmakova, A. ;

Shamkhalova, M. ;

Jarek-Martynowa, I ;

Artemova, E. ;

Beshlieva, D. ;

Bondarenko, O. ;

Volevodz, N. ;

Gomova, I ;

Grigoryan, O. ;

Dzhemilova, Z. ;

Esayan, R. ;

Ibragimova, L. ;

Kononenko, I ;

Kalashnikov, V ;

Laptev, D. ;

Lipatov, D. ;

Motovilin, O. ;

Nikonova, T. ;

Rozhivanov, R. ;

Shestakova, E. .

DIABETES MELLITUS, 2019, 22 (01) :1-143

[7] The prevalence of type 2 diabetes mellitus in the adult population of Russia (NATION study) [J].

Dedov, I. I. ;

Shestakova, M. V. ;

Galstyan, G. R. .

DIABETES MELLITUS, 2016, 19 (02) :104-112

[8]

Demidova TY, 2006, TERAPEVT ARKH, V78, P64

[9] Differences in Exhaled Gas Profiles Between Patients with Type 2 Diabetes and Healthy Controls [J].

Greiter, M. B. ;

Keck, L. ;

Siegmund, T. ;

Hoeschen, C. ;

Oeh, U. ;

Paretzke, H. G. .

DIABETES TECHNOLOGY & THERAPEUTICS, 2010, 12 (06) :455-463

[10] Fast-passage microwave molecular spectroscopy with frequency sweeping [J].

Khodos, VV ;

Ryndyk, DA ;

Vaks, VL .

EUROPEAN PHYSICAL JOURNAL-APPLIED PHYSICS, 2004, 25 (03) :203-208

← 1 2 3 4 →