RT Journal Article
SR Electronic
T1 Exhaled breath analysis by use of eNose technology: a novel diagnostic tool for interstitial lung disease
JF European Respiratory Journal
JO Eur Respir J
FD European Respiratory Society
SP 2002042
DO 10.1183/13993003.02042-2020
VO 57
IS 1
A1 Catharina C. Moor
A1 Judith C. Oppenheimer
A1 Gizal Nakshbandi
A1 Joachim G.J.V. Aerts
A1 Paul Brinkman
A1 Anke-Hilse Maitland-van der Zee
A1 Marlies S. Wijsenbeek
YR 2021
UL http://erj.ersjournals.com/content/57/1/2002042.abstract
AB Introduction Early and accurate diagnosis of interstitial lung diseases (ILDs) remains a major challenge. Better noninvasive diagnostic tools are much needed. We aimed to assess the accuracy of exhaled breath analysis using eNose technology to discriminate between ILD patients and healthy controls, and to distinguish ILD subgroups.Methods In this cross-sectional study, exhaled breath of consecutive ILD patients and healthy controls was analysed using eNose technology (SpiroNose). Statistical analyses were done using partial least square discriminant analysis and receiver operating characteristic analysis. Independent training and validation sets (2:1) were used in larger subgroups.Results A total of 322 ILD patients and 48 healthy controls were included: sarcoidosis (n=141), idiopathic pulmonary fibrosis (IPF) (n=85), connective tissue disease-associated ILD (n=33), chronic hypersensitivity pneumonitis (n=25), idiopathic nonspecific interstitial pneumonia (n=10), interstitial pneumonia with autoimmune features (n=11) and other ILDs (n=17). eNose sensors discriminated between ILD and healthy controls, with an area under the curve (AUC) of 1.00 in the training and validation sets. Comparison of patients with IPF and patients with other ILDs yielded an AUC of 0.91 (95% CI 0.85–0.96) in the training set and an AUC of 0.87 (95% CI 0.77–0.96) in the validation set. The eNose reliably distinguished between individual diseases, with AUC values ranging from 0.85 to 0.99.Conclusions eNose technology can completely distinguish ILD patients from healthy controls and can accurately discriminate between different ILD subgroups. Hence, exhaled breath analysis using eNose technology could be a novel biomarker in ILD, enabling timely diagnosis in the future.Exhaled breath analysis using eNose technology can accurately discriminate between different ILD subgroups and individual diseases. eNose technology could be a novel diagnostic tool in ILD, enabling timely diagnosis in the future. https://bit.ly/3jJs2hf