| Title: | Assessment of Electronic Sensing Techniques for the Rapid Identification of Alveolar Echinococcosis through Exhaled Breath Analysis |
| Author(s): | Kwiatkowski A; Chludzinski T; Saidi T; Welearegay TG; Jaimes-Mogollon AL; El Bari N; Borys S; Bouchikhi B; Smulko J; Ionescu R; |
| Address: | "Department of Metrology and Optoelectronics, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80233 Gdansk, Poland. Sensor Electronic & Instrumentation Group, Faculty of Sciences, Department of Physics, Moulay Ismail University of Meknes, B.P. 11201, Zitoune, Meknes 50050, Morocco. Biotechnology Agroalimentary and Biomedical Analysis Group, Faculty of Sciences, Department of Biology, Moulay Ismail University of Meknes, B.P. 11201, Zitoune, Meknes 50050, Morocco. Department of Electronics, Electrical and Automatic Engineering, Rovira i Virgili University, 43007 Tarragona, Spain. The Angstrom Laboratory, Division of Solid State Physics, Department of Materials Science and Engineering, Uppsala University, 75121 Uppsala, Sweden. GISM Group, Faculty of Engineering and Architecture, University of Pamplona, Pamplona 543050, Colombia. Department of Chemical Engineering, Complutense University of Madrid, 28040 Madrid, Spain. University Centre of Maritime and Tropical Medicine, 81519 Gdynia-Redlowo, Poland" |
| ISSN/ISBN: | 1424-8220 (Electronic) 1424-8220 (Linking) |
| Abstract: | "Here we present a proof-of-concept study showing the potential of a chemical gas sensors system to identify the patients with alveolar echinococcosis disease through exhaled breath analysis. The sensors system employed comprised an array of three commercial gas sensors and a custom gas sensor based on WO(3) nanowires doped with gold nanoparticles, optimized for the measurement of common breath volatile organic compounds. The measurement setup was designed for the concomitant measurement of both sensors DC resistance and AC fluctuations during breath samples exposure. Discriminant Function Analysis classification models were built with features extracted from sensors responses, and the discrimination of alveolar echinococcosis was estimated through bootstrap validation. The commercial sensor that detects gases such as alkane derivatives and ethanol, associated with lipid peroxidation and intestinal gut flora, provided the best classification (63.4% success rate, 66.3% sensitivity and 54.6% specificity) when sensors' responses were individually analyzed, while the model built with the AC features extracted from the responses of the cross-reactive sensors array yielded 90.2% classification success rate, 93.6% sensitivity and 79.4% specificity. This result paves the way for the development of a noninvasive, easy to use, fast and inexpensive diagnostic test for alveolar echinococcosis diagnosis at an early stage, when curative treatment can be applied to the patients" |
| Keywords: | Adult Aged *Breath Tests *Echinococcosis/diagnosis Electronics Female Gold Humans Male *Metal Nanoparticles Middle Aged *Volatile Organic Compounds AC fluctuation measurements DC resistance measurements breath analysis chemical gas sensors diagnosis echin; |
| Notes: | "MedlineKwiatkowski, Andrzej Chludzinski, Tomasz Saidi, Tarik Welearegay, Tesfalem Geremariam Jaimes-Mogollon, Aylen Lisset El Bari, Nezha Borys, Sebastian Bouchikhi, Benachir Smulko, Janusz Ionescu, Radu eng 645758/H2020 Marie Sklodowska-Curie Actions/ Switzerland 2020/05/13 Sensors (Basel). 2020 May 7; 20(9):2666. doi: 10.3390/s20092666" |
