PO100 - The role of electronic nose (e-nose) technology in ILD diagnosis and BAL cell discrimination
Eirini Vasarmidi (Greece)1; Athina Trachalaki (UK)1 2; Ioanna Argyriou (Greece)1; Rianne de Vries (Netherlands)3; Nikoleta Bizymi (Greece)1; Marilena Lourou (Greece)1; Konstantina Symvoulaki (Greece)1; Christian Hesslinger (Germany)4; Daniel Peter (Germany)4; Lutz Wollin (Germany)4; Eliza Tsitoura (Greece)1; Katerina M. Antoniou (Greece)1;
1 - Department of Respiratory Medicine, Laboratory of Molecular and Cellular Pneumonology, School of Medicine, University of Crete, Heraklion, Greece; 2 - National Heart and Lung Institute, Imperial College London, London, UK; 3 - Breathomix BV, Reeuwijk, The Netherlands; 4 - Boehinger Ingelheim Pharma GmbH & Co KG, Biberach, Germany;
Keywords: eNOSE; fibrotic ILD; BAL;
Select the theme: Fibrotic Pulmonary Interstitial Fibrosis
Type: Original Papers
Presentation: Poster Presentation

Introduction: The clinical differentiation of fibrotic interstitial lung diseases (ILDs) is complex due to their overlapping clinical presentations. While current diagnostic algorithms rely on high-resolution computed tomography (HRCT) and invasive procedures, these methods are often resource-intensive and lack efficiency. 

Objectives: This study investigates the diagnostic utility of electronic nose (e-nose) breath analysis as a non-invasive alternative for identifying ILD and its underlying patterns.

Materials and Methods: Exhaled breath was collected from 81 patients with fibrotic ILD and 17 healthy controls at the time of diagnosis. Analysis was performed using the SpiroNose (Breathomix) system. Conventional diagnostics, including lung function testing and bronchoalveolar lavage (BAL) cellularity, were conducted in parallel. Data processing involved advanced signal processing and ambient air correction. Statistical discrimination was performed using linear discriminant analysis (LDA) and evaluated via receiver operating characteristic (ROC) analysis.

Results: Breath profiles demonstrated high discriminatory capacity between healthy controls and ILD patients (ROC-AUC: 0.89). Furthermore, e-nose analysis successfully distinguished idiopathic pulmonary fibrosis (IPF, n=20) from non-IPF ILDs (n=61) with an AUC of 0.94. Specific sub-analyses showed high accuracy in differentiating IPF from connective tissue disease-associated ILD (CTD-ILD; AUC: 0.91) and chronic hypersensitivity pneumonitis (cHP; AUC: 0.82). Notably, breathprints could distinguish between the usual interstitial pneumonia (UIP) pattern and non-UIP patterns on HRCT (Accuracy: 65.4%; AUC: 0.72). Additionally, exhaled breath profiles significantly correlated with BAL cellularity; optimal thresholds were identified for lymphocytes (17%; AUC: 0.71), neutrophils (4%; AUC: 0.86), and eosinophils (3%; AUC: 0.82).

Conclusions: These findings validate exhaled breath analysis as a robust, non-invasive supportive tool for the diagnosis and characterisation of fibrotic ILDs. This study provides the first evidence that e-nose technology can reflect both radiological patterns (UIP) and BAL inflammatory profiles, suggesting that "breathprints" may serve as a viable surrogate marker for pulmonary pathology and cellularity.