Wavelength-swept spontaneous Raman spectroscopy system improves fiber-based collection efficiency for whole brain tissue classification

被引:0
作者
Parham, Elahe [1 ,2 ]
Rousseau, Antoine [1 ,2 ]
Quemener, Mireille [1 ,2 ]
Parent, Martin [1 ]
Cote, Daniel C. [1 ,2 ]
机构
[1] CERVO Brain Res Ctr, Quebec City, PQ, Canada
[2] Univ Laval, Ctr Opt Photon & Laser, Quebec City, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Raman spectroscopy; wavelength-swept; swept-source Raman spectroscopy; tissue identification; photon detection; SPECTRA; METHANOL; ETHANOL; PROTEIN;
D O I
10.1117/1.NPh.11.2.025007
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Significance Raman spectroscopy is a valuable technique for tissue identification, but its conventional implementation is hindered by low efficiency due to scattering. Addressing this limitation, we are further developing the wavelength-swept Raman spectroscopy approach. Aim We aim to enhance Raman signal detection by employing a laser capable of sweeping over a wide wavelength range to sequentially excite tissue with different wavelengths, paired with a photodetector featuring a fixed narrow-bandpass filter for collecting the Raman signal at a specific wavelength. Approach We experimentally validate our technique using a fiber-based swept-source Raman spectroscopy setup. In addition, simulations are conducted to assess the efficacy of our approach in comparison with conventional spectrometer-based Raman spectroscopy. Results Our simulations reveal that the wavelength-swept configuration leads to a significantly stronger signal compared with conventional spectrometer-based Raman spectroscopy. Experimentally, our setup demonstrates an improvement of at least 200x in photon detection compared with the spectrometer-based setup. Furthermore, data acquired from different regions of a fixed monkey brain using our technique achieves 99% accuracy in classification via k-nearest neighbor analysis. Conclusions Our study showcases the potential of wavelength-swept Raman spectroscopy for tissue identification, particularly in highly scattering media, such as the brain. The developed technique offers enhanced signal detection capabilities, paving the way for future in vivo applications in tissue characterization.
引用
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页数:13
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