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Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of lung cancer patients
  1. Michael Westhoff (michael.westhoff{at}
  1. Lung Clinic Hemer, Germany
    1. Patric Litterst (pneumologie{at}
    1. Lung Clinic Hemer, Germany
      1. Lutz Freitag (lutz.freitag{at}
      1. Lung Clinic Hemer, Germany
        1. Wolfgang Urfer
        1. Institute of Statistics,Technical University Dortmund, Germany
          1. Sabine Bader (s.bader{at}
          1. ISAS - Institute for Analytical Sciences, Germany
            1. Joerg Ingo Baumbach (j.i.baumbach{at}
            1. ISAS - Institute for Analytical Sciences, Germany


              Background: Analysis of exhaled breath, especially of volatile organic compounds (VOCs), is of increasing interest in the diagnosis of lung cancer. Compared to other methods of breath analysis, ion mobility spectrometry (IMS) offers a ten-fold higher detection rate of VOCs. By coupling the ion mobility spectrometer with a multi-capillary column as a pre-separation unit, IMS offers the advantage of an immediate two-fold separation of VOCs with visualisation in a three-dimensional chromatogram. The total analysis time is about 500 s compared to gas chromatography/mass spectrometry (GC/MS) of about 1 h. Therefore it seemed reasonable to test IMS in breath analysis.

              Methods: In this pilot study 32 patients with lung cancer were subjected to a breath analysis by IMS. Their IMS-chromatograms were compared with those of 54 healthy controls. An IMS that was built for special clinical application was used to identify characteristic peaks of VOCs , which might be relevant for the diagnosis of lung cancer in exhaled air of 10 mL volume.

              Results: By a combination of 23 peak regions within the IMS-Chromatogram, patients with lung cancer, including a patient with carcinoma in situ, were classified and differentiated from healthy persons with an error rate of 0.

              Conclusion: Breath analysis by IMS can detect a discriminating combination of VOCs in lung cancer patients. By pattern recognition without the need for chemical analysis of the underlying VOCs, IMS has the potential to facilitate lung cancer diagnosis.

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