Non-Invasive Diagnosis of Malignancies Based on the Analysis of Markers in Exhaled Air

Abstract

Background: Novel non-invasive methods for diagnosis of malignancies should be effective for early diagnosis, reproducible, inexpensive, and independent from the human factor. Our aim was to establish the applicability of the non-invasive method, based on analysis of air exhaled by patients who are at different stages of the oropharyngeal, larynx and lung cancer. Methods: The diagnostic device includes semiconductor sensors capable of measuring the concentration of gas components in exhaled air with the high sensitivity of 1 ppm. The neural network uses signals from these sensors to perform classification and identify cancer patients. Prior to the diagnostic procedure by the non-invasive method, we clarified the extent and stage of the tumor according to current international standards and recommendations for the diagnosis of malignancies. Findings: The statistical dataset for neural network training and method validation included samples from 121 patients. In our study, exhaled air samples were taken from groups of patients with the most common tumor localizations: lungs, oropharyngeal region and larynx. The largest number of cases (21 patients) were lung cancer, while the number of patients with oropharyngeal or laryngeal cancer varied from 1 to 9 depending on tumor localization (oropharyngeal, tongue, oral cavity, larynx and mucosa of the lower jaw). In the case of lung cancer, the parameters of the diagnostic device are determined as follows: sensitivity – 95.24 %, specificity – 76.19 %. For oropharyngeal cancer and laryngeal cancer, these parameters were 67.74 % and 87.1 %, respectively. Interpretation: This non-invasive method could lead to relevant in medicine findings and provide to opportunity of clinical utility and patient benefit on early diagnosis of malignancies. Further research should be focused on other localizations of malignancies, distinguishing different types of cancer, as well as the variability of samples and sampling technique. Funding: The Federal target program of the Ministry of Science and higher Education of the Russian Federation, RFMEFI60419X0221. Declaration of Interests: No potential conflicts of interest were disclosed. Ethics Approval Statement: The study was approved by the Bioethical Committee of the Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences (Order on creation No. 57-p dated 23.12.2010).