Breath analysis is increasingly recognized as a powerful noninvasive diagnostic technique, and a plethora of exhaled volatile biomarkers have been associated with various diseases. However, traditional analytical methodologies are not amenable to high-throughput diagnostic applications at the point of need. An optical spectroscopic technique, surface-enhanced Raman spectroscopy (SERS), mostly used in the research setting for liquid sample analysis, has recently been applied to breath-based diagnostics. This promising noninvasive diagnostic tool has been demonstrated for the identification of various diseases, including lung cancer, gastric cancer, and diabetes. The versatility of SERS has enabled the use of different diagnostic strategies and allowed for fast and accurate detection of small analytes in exhaled breath. In this review, we provide an overview of recent advances in SERS-based breath analysis, focusing on sensors for the detection of gases and volatile organic compounds (VOCs) in exhaled breath, and highlight generic strategies for sample preconcentration and methods for spectral analysis. We aim to provide an overview of the state of the art and inspiration for further SERS investigation of expiration.
Keywords: Breath; Machine Learning; Microfluidics; Nanomaterials; Preconcentrators; Sensors; Surface-Enhanced Raman Spectroscopy (SERS); Volatile Organic Compounds (VOCs).