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Updated: Aug 12, 2026

Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems
Published on: February 10, 2020
Relevance of light conditions for clinical in situ Raman spectroscopy
Sven Richter1,2, Sotirios Kalousios1,2, Roberta Galli3
1Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Background:
Clinical Raman spectroscopy is a promising optical technology for intraoperative brain tumor delineation and diagnosis. As it exploits weak signals, illumination of the operating room (OR) and OR devices might impact the acquired spectra. The aim of this study was to investigate which optical artifacts can be tolerated during the intraoperative analysis of brain tumors in situ while still allowing the extraction of meaningful Raman spectra.
Methods:
Tissue samples of rat brain and human brain tumors were investigated in an experimental OR, and background signals and Raman spectroscopic datasets were acquired using a fiber-based system. The measurements were performed under various lighting conditions and OR equipment.
Results:
Ceiling light intensity increased the background, which could be prevented by manual coverage. Hence, the signal-to-noise-ratio of Raman spectra was not altered by ceiling lights. The intensity of the raw spectra of brain tissue and glioma was determined mainly by tissue autofluorescence and not by OR illumination, but it substantially affected the raw spectra of meningioma having low autofluorescence. Operating (OP) lights lead to saturation of the Raman camera. The exoscope, displays, and optical neuronavigation systems produced spectrally structured artifacts. Correct background subtraction was sufficient for artifact correction and obtaining valid Raman spectra.
Conclusions:
For clinical Raman spectroscopy, it is of utmost importance to be aware of optical disturbances. Intense illumination needs to be avoided but (spectrally structured) disturbances can be corrected by data preprocessing. Rather than external illumination, strong tissue autofluorescence might lead to impaired Raman spectral quality, making tumor tissue recognition difficult.
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