Advances in real‐time fiber‐optic Raman spectroscopy for early cancer diagnosis: Pushing the frontier into clinical endoscopic applications. Issue 1 (6th October 2020) - Heng, Howard Peng Sin; Shu, Chi; Zheng, Wei; Lin, Kan; Huang, Zhiwei
Abstract: Real‐time fiber‐optic Raman spectroscopy has emerged as a compelling approach for biomedical diagnosis and characterization. This article reviews the following topics related to real‐time in vivo clinical Raman system development, such as (a) modern Raman instrumentation; (b) current developments in miniaturized fiber‐optic Raman probe designs and fabrications and (c) data processing techniques, artificial intelligence and machine learning for Raman classification and diagnosis. These synergistic advances over the past few decades play a central role in developing this unique label‐free biomolecular probe into a clinically relevant tool. The growing body of clinical literature at in vivo Raman endoscopy is an embodiment of an emerging powerful diagnostic technique that would revolutionize the future of healthcare in medicine. The past two decades of Raman endoscopic work are summarized with an emphasis on in vivo studies, illustrating the promising potential of real‐time fiber‐optic Raman spectroscopy to improve the early detection and diagnosis of precancer and cancer in vivo during clinical endoscopic examination. The challenges that exist in the widespread clinical implementation of this unique Raman diagnostic tool will be discussed, and the potential outlook in biomedical applications will also be outlined, particularly in endoscopy. Abstract : Modern Raman instrumentation for real‐time, in vivo clinical Raman measurements and diagnosis. The Raman system consist of a depth‐resolved optical fiber probe that can fit into the instrument channel of a medical endoscope, a sensitive Raman spectrometer that can acquire both the fingerprint and high‐wavenumber spectral information simultaneously, and a robust machine learning algorithms to provide accurate Raman diagnosis in real time at endoscopy.