Feasibility of electronic nose technology for discriminating between head and neck, bladder, and colon carcinomas.

Autor: van de Goor RM; Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands. rens.vande.goor@mumc.nl., Leunis N; Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands., van Hooren MR; Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands., Francisca E; Department of Urology, Maastricht University Medical Center, Maastricht, The Netherlands., Masclee A; Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht, The Netherlands., Kremer B; Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands., Kross KW; Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands.
Jazyk: angličtina
Zdroj: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery [Eur Arch Otorhinolaryngol] 2017 Feb; Vol. 274 (2), pp. 1053-1060. Date of Electronic Publication: 2016 Oct 11.
DOI: 10.1007/s00405-016-4320-y
Abstrakt: Electronic nose (e-nose) technology has the potential to detect cancer at an early stage and can differentiate between cancer origins. Our objective was to compare patients who had head and neck squamous cell carcinoma (HNSCC) with patients who had colon or bladder cancer to determine the distinctive diagnostic characteristics of the e-nose. Feasibility study An e-nose device was used to collect samples of exhaled breath from patients who had HNSCC and those who had bladder or colon cancer, after which the samples were analyzed and compared. One hundred patients with HNSCC, 40 patients with bladder cancer, and 28 patients with colon cancer exhaled through an e-nose for 5 min. An artificial neural network was used for the analysis, and double cross-validation to validate the model. In differentiating HNSCC from colon cancer, a diagnostic accuracy of 81 % was found. When comparing HNSCC with bladder cancer, the diagnostic accuracy was 84 %. A diagnostic accuracy of 84 % was found between bladder cancer and colon cancer. The e-nose technique using double cross-validation is able to discriminate between HNSCC and colon cancer and between HNSCC and bladder cancer. Furthermore, the e-nose technique can distinguish colon cancer from bladder cancer.
Competing Interests: Each author has participated sufficiently in the present study. The authors of this article had access to all study data, are responsible for all contents of the article, and had authority over manuscript preparation and the decision to submit the manuscript for publication. The authors of this study did not and will not receive any financial support of companies, associations, or organizations. The authors have no other conflicts of interest. Ethical approval All procedures involving human participants were performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Databáze: MEDLINE
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