International validation of electronic nose technology as a diagnostic tool for fibrotic interstitial lung diseases
Bart J Formsma1, Iris G van der Sar1, Leda Yazbeck2,3
1Department of Respiratory Medicine, Center of Excellence for ILD and Sarcoidosis, Erasmus University Medical Center, Rotterdam, The Netherlands.
Introduction:
Fibrotic interstitial lung diseases (fILDs) are a heterogeneous group of rare lung diseases. Symptoms of ILD are nonspecific, and diagnosis requires multiple investigations, including invasive procedures. Therefore, diagnostic delay is common. Previous single-center studies showed that profiling of exhaled volatile organic compounds using noninvasive electronic nose (eNose) sensor technology has potential as a diagnostic tool for ILD. We aimed to validate eNose technology to differentiate various ILDs in an international multicenter cohort.
Methods:
We included patients with an ILD diagnosis established in a multidisciplinary team (MDT) discussion and pulmonary fibrosis on high-resolution chest computed tomography scans at 5 international ILD expert centers. An eNose (SpiroNose) was used for exhaled breath analysis. We compared eNose breath profiles of different ILD subtypes with all other ILDs combined and across 6 different ILD subtypes. Breath profiles were analyzed with partial least squares discriminant and receiver operating characteristic analyses. Models were trained on data from a selection of centers and externally validated in other centers.
Results:
Breath profiles of 587 patients were analyzed. Comparing breath profiles of ILD subtypes with all other ILDs resulted in area under the curve (AUC) values ranging from 0.88 to 0.92 in the training set and 0.75 to 0.95 in the validation set. The ILD subtypes could be discriminated with AUCs ranging from 0.95 to 0.98 in the training set and 0.83 to 0.93 in the validation set.
Discussion:
This international study demonstrates that eNose technology accurately differentiates breath profiles from -patients with various ILDs. eNose technology holds potential as an easy point-of-care tool for the diagnosis of fILDs.
