Diagnostic Performance of Electronic Nose Technology in Sarcoidosis.

BACKGROUND: Diagnosing sarcoidosis can be challenging, and a noninvasive diagnostic method is lacking. The electronic nose (eNose) technology profiles volatile organic compounds in exhaled breath and has potential as a point-of-care diagnostic tool. RESEARCH QUESTION: Can eNose technology be used to distinguish accurately between sarcoidosis, interstitial lung disease (ILD), and healthy control subjects, and between sarcoidosis subgroups? STUDY DESIGN AND METHODS: In this cross-sectional study, exhaled breath of patients with sarcoidosis and ILD and healthy control subjects was analyzed by using an eNose (SpiroNose). Clinical characteristics were collected from medical files. Partial least squares discriminant and receiver-operating characteristic analyses were applied to a training and independent validation cohort. RESULTS: The study included 252 patients with sarcoidosis, 317 with ILD, and 48 healthy control subjects. In the validation cohorts, eNose distinguished sarcoidosis from control subjects with an area under the curve (AUC) of 1.00 and pulmonary sarcoidosis from other ILD (AUC, 0.87; 95% CI, 0.82-0.93) and hypersensitivity pneumonitis (AUC, 0.88; 95% CI, 0.75-1.00). Exhaled breath of sarcoidosis patients with and without pulmonary involvement, pulmonary fibrosis, multiple organ involvement, pathology-supported diagnosis, and immunosuppressive treatment revealed no distinctive differences. Breath profiles differed between patients with a slightly and highly elevated soluble IL-2 receptor level (median cutoff, 772.0 U/mL; AUC, 0.78; 95% CI, 0.64-0.92). INTERPRETATION: Patients with sarcoidosis can be distinguished from ILD and healthy control subjects by using eNose technology, indicating that this method may facilitate accurate diagnosis in the future. Further research is warranted to understand the value of eNose in monitoring sarcoidosis activity.

Exhaled breath analysis by use of eNose technology: a novel diagnostic tool for interstitial lung disease.

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.