BIONOTE e-nose technology may reduce false positives in lung cancer screening programmes†.

OBJECTIVES Breath composition may be suggestive of different conditions. E-nose technology has been used to profile volatile organic compounds (VOCs) pattern in the breath of patients compared with that of healthy individuals. BIOsensor-based multisensorial system for mimicking NOse, Tongue and Eyes (BIONOTE) technology differs from Cyranose® based on a set of separate transduction features. On the basis of our previously published experience, we investigated the discriminating ability of BIONOTE in a high-risk population enrolled in a lung cancer screening programme. METHODS One hundred individuals were selected for BIONOTE based on the attribution to the high-risk category (i.e. age, smoking status, chronic obstructive pulmonary disease status) of the University Campus Bio-Medico lung screening programme. We used a measure chain consisting of (i) a device named Pneumopipe (EU patent: EP2641537 (A1):2013-09-25) able to catch exhaled breath by an individual normally breathing into it and collect the exhalate onto an adsorbing cartridge; (ii) an apparatus for thermal desorption of the cartridge into the sensors chamber and (iii) a gas sensor array which is part of a sensorial platform named BIONOTE for the VOCs mixture analysis. Partial least square (PLS) has been used to build up the model, with Leave-One-Out cross-validation criterion. Each breath fingerprint analysis costs €10. RESULTS The overall sensitivity and specificity were 86 and 95%, respectively, delineating a substantial difference between patients and healthy individuals. CONCLUSIONS Our preliminary data show that BIONOTE technology may be used to reduce false-positive rates resulting from lung cancer screening with low-dose computed tomography in a cost-effective fashion. The model will be tested on a larger number of patients to confirm the reliability of these results.

[1]  P. V. Van Schil,et al.  Clinical statement on the role of the surgeon and surgical issues relating to computed tomography screening programs for lung cancer. , 2013, The Annals of thoracic surgery.

[2]  John K. Field,et al.  Perspective: The screening imperative , 2014, Nature.

[3]  Calum E. MacAulay,et al.  Sex and Smoking Status Effects on the Early Detection of Early Lung Cancer in High-Risk Smokers Using an Electronic Nose , 2015, IEEE Transactions on Biomedical Engineering.

[4]  J. Austin,et al.  Detection of lung cancer using weighted digital analysis of breath biomarkers. , 2008, Clinica chimica acta; international journal of clinical chemistry.

[5]  C. Gatsonis,et al.  Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening , 2012 .

[6]  Giorgio Pennazza,et al.  Reproducibility and Respiratory Function Correlates of Exhaled Breath Fingerprint in Chronic Obstructive Pulmonary Disease , 2012, PloS one.

[7]  Matthijs Oudkerk,et al.  Prospects for population screening and diagnosis of lung cancer , 2013, The Lancet.

[8]  R. Cataneo,et al.  Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study , 1999, The Lancet.

[9]  M. Santonico,et al.  Detection and identification of cancers by the electronic nose. , 2012, Expert opinion on medical diagnostics.

[10]  R. Jewkes,et al.  Perceptions and Experiences of Research Participants on Gender-Based Violence Community Based Survey: Implications for Ethical Guidelines , 2012, PloS one.

[11]  S. Blackmon,et al.  The United States Preventive Services Task Force recommendations for lung cancer screening. , 2015, Thoracic surgery clinics.

[12]  Giorgio Pennazza,et al.  An investigation on electronic nose diagnosis of lung cancer. , 2010, Lung cancer.

[13]  U. Pastorino,et al.  Refining strategies to identify populations to be screened for lung cancer. , 2015, Thoracic surgery clinics.

[14]  Panpan Qiao,et al.  Advances in the early detection of lung cancer using analysis of volatile organic compounds: from imaging to sensors. , 2014, Asian Pacific journal of cancer prevention : APJCP.

[15]  I. Horváth,et al.  Exhaled biomarkers in lung cancer , 2009, European Respiratory Journal.

[16]  D. Hansell,et al.  European and North American lung cancer screening experience and implications for pulmonary nodule management , 2011, European Radiology.

[17]  C Di Natale,et al.  In situ detection of lung cancer volatile fingerprints using bronchoscopic air-sampling. , 2012, Lung cancer.

[18]  H. Groen,et al.  Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals , 2013, European Radiology.

[19]  G. Hunter,et al.  Smart sensor systems for human health breath monitoring applications. , 2011, Journal of breath research.

[20]  C. la Vecchia,et al.  Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[21]  M. Phillips,et al.  Variation in volatile organic compounds in the breath of normal humans. , 1999, Journal of chromatography. B, Biomedical sciences and applications.

[22]  E. Martinelli,et al.  Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. , 2003, Biosensors & bioelectronics.

[23]  Giorgio Pennazza,et al.  Narrowing the gap between breathprinting and disease diagnosis, a sensor perspective , 2013 .

[24]  Giorgio Pennazza,et al.  Design and Test of a Biosensor-Based Multisensorial System: A Proof of Concept Study , 2013, Sensors.

[25]  David R. Jones,et al.  Results of the national lung cancer screening trial: where are we now? , 2015, Thoracic surgery clinics.

[26]  B. Meyers,et al.  Health risks from computed tomographic screening. , 2015, Thoracic surgery clinics.