Exhaled Breath Analysis for Detecting Interstitial Lung Diseases

The results of this thesis highlight the promising potential of eNose technology as a non-invasive diagnostic tool for respiratory diseases. By leveraging the power of breathomics, the SpiroNose offers a novel approach to accurately capture metabolic signatures linked to conditions like asthma, COPD, and lung cancer. Unlike traditional diagnostic methods that may miss early disease signs or struggle with heterogeneous phenotypes, the SpiroNose has demonstrated a high level of accuracy and reproducibility in identifying distinct disease profiles.

This technology provides real-time insights, making it a valuable addition to routine clinical practice. The integration of eNose analysis with spirometry not only enhances diagnostic precision but also enables rapid decision-making at the point of care. The ability to monitor inflammatory phenotypes and predict responses to therapy further underscores its potential in personalized medicine.

While additional validation is necessary to standardize the approach across diverse patient populations, the current findings are highly encouraging. The SpiroNose has the capacity to transform the diagnostic landscape of respiratory medicine, paving the way for earlier intervention, tailored treatment strategies, and ultimately better patient outcomes. As we continue to refine and validate this technology, it stands to set a new standard in non-invasive respiratory diagnostics.