title: Integrated statistical learning  of metabolic ion mobility spectrometry profiles for  pulmonary disease identification.
abstract: Exhaled  air carries information on human health status. Ion mobility spectrometers  combined with a multi-capillary column (MCC/IMS) is a well-known technology for  detecting volatile organic compounds (VOCs) within human breath. This technique  is relatively inexpensive, robust and easy to use in every day practice.  However, the potential of this methodology depends on successful application of  computational approaches for finding relevant VOCs and classification of  patients into disease-specific profile groups based on the detected VOCs. We  developed an integrated state-of-the-art system using sophisticated statistical  learning techniques for VOC-based feature selection and supervised classification  into patient groups. We analyzed breath data from 84 volunteers, each of them  either suffering from chronic obstructive pulmonary disease (COPD), or both  COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy  volunteers, comprising a control group (CG). We standardized and integrated  several statistical learning methods to provide a broad overview of their  potential for distinguishing the patient groups. We found that there is strong  potential for separating MCC/IMS chromatograms of healthy controls and COPD  patients (best accuracy COPD vs CG: 94%). However, further examination  of the impact of bronchial carcinoma on COPD/no-COPD classification performance  is necessary (best accuracy CG vs COPD vs COPD + BC: 79%). We  also extracted 20 high-scoring VOCs that allowed differentiating COPD patients  from healthy controls. We conclude that these statistical learning methods have  a generally high accuracy when applied to well-structured, medical MCC/IMS  data.
authors.affiliation: Department Microfluidics and Clinical Diagnostics, KIST Europe, Saarbrücken, Germany.
authors.forename: A-C
authors.initials: AC
authors.lastname: Hauschild
authors.forename: J I
authors.initials: JI
authors.lastname: Baumbach
authors.forename: J
authors.initials: J
authors.lastname: Baumbach
mesh_terms: D001984:Bronchial Neoplasms / Q000150:complications / Q000378:metabolism; D016022:Case-Control Studies; D006801:Humans; D007477:Ions; D013058:Mass Spectrometry / Q000379:methods*; D055442:Metabolome; D015233:Models, Statistical; D029424:Pulmonary Disease, Chronic Obstructive / Q000145:classification / Q000150:complications / Q000175:diagnosis* / Q000378:metabolism*; D060388:Support Vector Machine
chemical_list: D007477:Ions