2023   01   az   p.03-09 A.H. Aydemirova1, L.A. Melikova1,2, O.K. Gasymov1,
Diagnostic possibilities of the plasma-lipid model in healthy people and patients with lung adenocarcinoma using FT-IR spectroscopy


In our previous study, artificial intelligence technique has been applied for analysis of FT-IR spectra of human blood plasma samples to classify carcinoma and healthy people. Various statistical methods, such as “Linear SVM” (support vector machine), “PLS-DA” (partially square discriminant analysis) and “Random Forest” were used for classification to distinguish a group of patients and healthy people. Prediction accuracies were 90% and 80%, respectively. In this study, the increase molecular features that differentiate healthy and cancer patients, FT-IR spectra of both plasma and its lipid fractions were analyzed. Numerous spectral peaks of lipid fraction are not seen in blood plasma FT-IR spectra. Functional groups identified from FT-IR spectra of the lipid fraction of blood plasma make valuable impact for accurate classification. In the study, blood plasma samples were collected from 50 patients and 49 healthy individuals. Then, lipids were extracted for each plasma sample. Coupled analysis was performed for FT-IR spectra of the plasma and its corresponding lipid fractions. For both groups the greatest differences in plasma and lipid fractions FT-IR spectra were observed around 3280 sm-1, 3060 sm-1, 2960 sm-1, 2930 sm-1, 1245 sm-1 and 3016 sm-1, 2920 sm-1, 1650 sm-1, 1214 sm-1, respectively. The data remaining outside the standard deviations in the infrared spectra of plasma and lipid samples allow it to be used as a preliminary diagnostic marker in determining the disease. The work in progress to apply artificial intelligence technique for detailed classification.

Keywords: lung adenocarcinoma, blood plasma, blood plasma lipids, FCHIG spectroscopy.
PACS: 87.64.Ve


Received: 09.12.2022


1. Institute of Biophysics, Ministry of Science and Education Republic of Azerbaijan 117 Z. Khalilov, Baku, AZ 1141
2. National Oncology Center of the Ministry of Health of the Republic of Azerbaijan, 79B H. Zardabi Street
E-mail: oktaygasimov@gmail.com

Graphics and Images


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