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Analysis of breath samples for lung cancer survival
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
Linköping University, Department of Physics, Chemistry and Biology, Biosensors and Bioelectronics. Linköping University, The Institute of Technology.
Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Respiratory Medicine.
2014 (English)In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 840, 82-86 p.Article in journal (Refereed) Published
Abstract [en]

Analyses of exhaled air by means of electronic noses offer a large diagnostic potential. Such analyses are non-invasive; samples can also be easily obtained from severely ill patients and repeated within short intervals. Lung cancer is the most deadly malignant tumor worldwide, and monitoring of lung cancer progression is of great importance and may help to decide best therapy. In this report, twenty-two patients with diagnosed lung cancer and ten healthy volunteers were studied using breath samples collected several times at certain intervals and analysed by an electronic nose. The samples were divided into three sub-groups; group d for survivor less than one year, group s for survivor more than a year and group h for the healthy volunteers. Prediction models based on partial least square and artificial neural nets could not classify the collected groups d, s and h, but separated well group d from group h. Using artificial neural net, group d could be separated from group s. Excellent predictions and stable models of survival day for group d were obtained, both based on partial least square and artificial neural nets, with correlation coefficients 0.981 and 0.985, respectively. Finally, the importance of consecutive measurements was shown.

Place, publisher, year, edition, pages
Elsevier Masson , 2014. Vol. 840, 82-86 p.
Keyword [en]
Breath analysis; Electronic nose; Lung cancer; Survival prediction
National Category
Clinical Medicine Biological Sciences
URN: urn:nbn:se:liu:diva-109871DOI: 10.1016/j.aca.2014.05.034ISI: 000339992500011PubMedID: 25086897OAI: diva2:741630

Funding Agencies|County Council of Ostergotland

Available from: 2014-08-28 Created: 2014-08-28 Last updated: 2014-08-28

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Schmekel, BirgittaWinquist, FredrikVikström, Anders
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Division of Cardiovascular MedicineFaculty of Health SciencesDepartment of Clinical Physiology in LinköpingBiosensors and BioelectronicsThe Institute of TechnologyDepartment of Clinical and Experimental MedicineDepartment of Respiratory Medicine
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Analytica Chimica Acta
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