Diagnosing Interstitial Lung Disease Using eNose Technology

interstitial pulmonary fibrosis
The use of exhaled breath analysis via eNose technology can help accurately distinguish various subtypes of interstitial lung disease.

The use of exhaled breath analysis via eNose technology can help accurately distinguish various subtypes of interstitial lung disease (ILD) and can differentiate patients with ILD from healthy individuals. Researchers conducted a single-center, cross-sectional study at the Erasmus Medical Center in Rotterdam, the Netherlands, and the results were published in the European Respiratory Journal.

Investigators sought to evaluate the accuracy of exhaled breath analysis using eNose technology to distinguish ILD subgroups and to identify patients with ILD vs healthy individuals. Statistical analyses were preformed via use of partial least square discriminant analysis and receiver operating characteristic curve.

Between July 2019 and February 2020, consecutive outpatients who had a diagnosis of ILD, based on American Thoracic Society/European Respiratory Society criteria, or a diagnosis of sarcoidosis, according to World Association of Sarcoidosis and Other Granulomatous Disorders criteria, were eligible for study enrollment. A total of 322 consecutive patients with ILD and 48 healthy control individuals were included in the study. The overall mean age of the patients with ILD was 61.6 years. Overall, 59.9% of the participants were men, and 5.3% were current smokers.

Patients with ILD were categorized into 7 subgroups: (1) idiopathic pulmonary fibrosis (IPF; n=85), (2) sarcoidosis (n=141), (3) connective tissue disease-associated ILD

(n=33), (4) chronic hypersensitivity pneumonitis (n=25), (5) interstitial pneumonia with autoimmune features (n=11), (6) idiopathic nonspecific interstitial pneumonia (n=10), and (7) other ILDs (n=17). All participants completed a short survey regarding relevant factors, including smoking history and food intake within the last 2 hours. Medical records were used to access data on medication use, lung function tests, radiology, pathology results, and recent laboratory parameters.

The eNose sensors differentiated between patients with ILD and healthy control individuals, with an area under the curve (AUC) of 1.0 in the training and validation sets. When patients with IPF were compared with those with other ILDs, the analysis 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. Further, use of the eNose technology reliably distinguished between individual subtypes of ILD, with AUCs ranging from 0.85 to 0.99 being reported.

A major limitation of the current study is the fact that the healthy control individuals were much younger, mainly women, and nonsmokers compared with those with various ILD subtypes. Nonetheless, the investigators concluded that exhaled breath analysis using eNose technology could prove to be a novel biomarker in patients with ILD, thus facilitating a timely diagnosis of the disease in the future.

Disclosure: This study was supported by Boehringer-Ingelheim. Please see the original reference for a full list of authors’ disclosures.


Moor CC, Oppenheimer JC, Nakshbandi G, et al. Exhaled breath analysis by use of eNose technology: a novel diagnostic tool for interstitial lung disease. Eur Respir J.         Published online July 30, 2020. doi:10.1183/13993003.02042-2020