Abstract
The Multi-capillary-column-Ion-mobility-spectrometry (MCC-IMS) technology for measuring breath gas can be used for distinguishing between healthy and diseased subjects or between different types of diseases. The statistical methods for classifying the corresponding breath samples typically neglects potential confounding clinical and technical variables, reducing both accuracy and generalizability of the results. Especially measuring samples on different technical devices can heavily influence the results. We conducted a controlled breath gas study including 49 healthy volunteers to evaluate the effect of the variables sex, smoking habits and technical device. Every person was measured twice, once before and once after consuming a glass of orange juice. The two measurements were obtained on two different devices. The evaluation of the MCC-IMS data regarding metabolite detection was performed once using the software VisualNow, which requires manual interaction, and once using the fully automated algorithm SGLTR-DBSCAN. We present statistical solutions, peak alignment and scaling, to adjust for the different devices. For the other potential confounders sex and smoking, in our study no significant influence was identified.
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