Exhaled Breath Analysis (EBA): A Comprehensive Review of Non-Invasive Diagnostic Techniques for Disease Detection

Exhaled breath analysis (EBA) is an advanced, non-invasive diagnostic technique that utilizes volatile organic compounds (VOCs) to detect and monitor various diseases. This review examines EBA’s historical development and current status as a promising diagnostic tool. It highlights the significant contributions of modern methods such as gas chromatography–mass spectrometry (GC-MS), ion mobility spectrometry (IMS), and electronic noses in enhancing the sensitivity and specificity of EBA. Furthermore, it emphasizes the transformative role of nanotechnology and machine learning in improving the diagnostic accuracy of EBA. Despite challenges such as standardization and environmental factors, which must be addressed for the widespread adoption of this technique, EBA shows excellent potential for early disease detection and personalized medicine. The review also highlights the potential of photonic crystal fiber (PCF) sensors, known for their superior sensitivity, in the field of EBA.

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Publication Details

Journal
Photonics
Published
2025-08-25
DOI
https://doi.org/10.3390/photonics12090848
Citations
4
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
2.70
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article

Exhaled Breath Analysis (EBA): A Comprehensive Review of Non-Invasive Diagnostic Techniques for Disease Detection

Sajjad Mortazavi, Karim Abbasian, Somayeh Makouei, Sebelan Danishvar
4 citations
Photonics
Advanced Chemical Sensor Technologies
2.70
article

Exhaled Breath Analysis (EBA): A Comprehensive Review of Non-Invasive Diagnostic Techniques for Disease Detection

Sajjad Mortazavi, Karim Abbasian, Somayeh Makouei, Sebelan Danishvar
article en
4 citations

Abstract

Exhaled breath analysis (EBA) is an advanced, non-invasive diagnostic technique that utilizes volatile organic compounds (VOCs) to detect and monitor various diseases. This review examines EBA’s historical development and current status as a promising diagnostic tool. It highlights the significant contributions of modern methods such as gas chromatography–mass spectrometry (GC-MS), ion mobility spectrometry (IMS), and electronic noses in enhancing the sensitivity and specificity of EBA. Furthermore, it emphasizes the transformative role of nanotechnology and machine learning in improving the diagnostic accuracy of EBA. Despite challenges such as standardization and environmental factors, which must be addressed for the widespread adoption of this technique, EBA shows excellent potential for early disease detection and personalized medicine. The review also highlights the potential of photonic crystal fiber (PCF) sensors, known for their superior sensitivity, in the field of EBA.

PhotonicsVol. 12(9)
University of Tabriz (IR), Brunel University of London (GB)
Openalex Percentile: Top 10%
Advanced Chemical Sensor Technologies
2.70
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