Exhaled breath analysis in interstitial lung disease
Aim: There is a need for better noninvasive tools to diagnose interstitial lung disease (ILD) and predict disease course. Volatile organic compounds present in exhaled breath contain valuable information on a person’s health and may be a novel biomarker in ILD. In this review, the authors give an overview of the basic principles of breath analysis, summarize the available evidence in ILD, and discuss future perspectives.
Take home message: The majority of studies using exhaled breath analysis in ILD show promising results for diagnostic purposes, but validation studies are lacking. Larger prospective longitudinal studies using standardized methods are needed to collect the evidence required for developing an approved diagnostic medical test.
Introduction
Interstitial lung diseases (ILDs) encompass over 200 different lung conditions characterized by inflammation, fibrosis, or both, affecting the lung interstitium. Diagnosing ILD is challenging due to nonspecific symptoms like dyspnea and cough. Traditional diagnostic methods often require invasive procedures and have limitations, leading to delays in diagnosis. Recent research has focused on exhaled breath analysis as a non-invasive approach, with volatile organic compounds (VOCs) in exhaled breath showing potential as biomarkers. This paper reviews current evidence on exhaled breath analysis using gas chromatography-mass spectrometry (GC-MS) and electronic nose (eNose) technology for diagnosing and monitoring ILD.
Methods
Two main techniques for breath analysis are discussed: GC-MS and eNose. GC-MS in some cases identifies specific VOCs in exhaled breath through separation and mass detection, providing detailed chemical analysis but requiring complex lab procedures, highly trained personnel and is costly and time-consuming. eNose technology, in contrast, captures breath profiles using sensor arrays that respond to different VOC patterns. This non-targeted approach creates a unique “breathprint” for each patient, allowing rapid, real-time analysis suitable for point-of-care diagnostics. Several studies have been conducted using these methods to assess their diagnostic performance in ILD populations.
Results
Studies using GC-MS and eNose technology in ILD patients showed promising results. GC-MS analysis identified multiple VOCs associated with different ILDs, with an area under the curve (AUC) ranging from 0.76 to 0.91 for distinguishing between ILD subtypes and healthy controls in small studies. eNose technology demonstrated high diagnostic accuracy, particularly in differentiating idiopathic pulmonary fibrosis (IPF) from other ILDs and different ILDs versus healthy controls, with accuracies exceeding 90%. The ability of eNose to classify ILD patients based on disease behavior and predict response to treatments like immunosuppressants and antifibrotics was also explored, showing AUC values of 0.75 to 0.84.
Discussion
Exhaled breath analysis, especially with eNose technology, shows significant potential as a non-invasive diagnostic tool for ILD. The rapid, real-time profiling capability of eNose devices makes them ideal for clinical applications, including early diagnosis, disease phenotyping, and monitoring of treatment response. Unlike GC-MS, eNose technology does not require identification of individual VOCs, reducing complexity and allowing for faster analysis. However, further validation studies with standardized methods across diverse patient populations are needed before these technologies can be fully integrated into clinical practice. Future research should focus on large-scale, multicenter trials to confirm the diagnostic and prognostic utility of breath analysis in ILD.
This summary highlights the potential of exhaled breath analysis in transforming the diagnostic landscape of interstitial lung diseases, paving the way for more efficient, non-invasive patient care.
