拉曼光谱技术在病理诊断中的研究进展

Raman spectroscopy can provide the spectral information related to the specific molecular structure of the substance, and recognize the tiny biochemical variation of biological tissue. It is a promising diagnosis technology in clinical applications due to the advantages of fast, real-time, non-destructive detection without sample pretreatment. Compared with the routine histopathological analysis, Raman spectroscopy can detect the fresh tissue directly and it may simplify the analysis procedure and shorten the diagnosis time. Some changes may take place in molecular composition and structure of pathological tissues, which provides a theoretical basis for the application of Raman spectroscopy in histopathological diagnosis. Raman spectroscopy may provide the objective diagnosis information and achieve the rapid, low-invasive diagnosis based on the differences of molecular composition and structure between normal and pathological tissues. This paper reviewed the development of Raman spectroscopy for the pathological diagnosis of tissues in the past decade and focused on the crucial results. Some key issues in the ex vivo and in vivo studies of Raman spectroscopy in pathological diagnosis were emphasized. Firstly, for the Raman detection of ex vivo sample, the applicability of several tissue samples, such as formal infixed paraffin-embedded samples, frozen samples and fresh tissue samples, was mainly evaluated; And the emphasis of Ramandata collection in the ex vivo studies of Raman spectroscopy, including applicable laser source, spectra range, and the way of spectra collection were summarized. Meanwhile, we focused on the two application forms of Raman spectroscopy in the detection in vivo, which involved the detection of Raman spectroscopy combined with the medical endoscope, and the direct detection in open surgery. The Raman system suitable for clinical application was also taken into consideration in this review, and the fiber probes used in the current in vivo Raman studies were major. Furthermore, the analysis methods of Raman data were discussed, the pathological diagnosis models, which can provide the excellent diagnosis results in the sample set with small size, have been established through spectral preprocessing, feature extraction, classification and identification. It is necessary to optimize the analysis method to achieve the correlation between Raman spectraand biochemical information and incorporate the effects of individual differences into the classification model to improve the model. In this paper, the crucial issues of Raman spectroscopy in pathological diagnosis were discussed in order to provide a reference for further research. More extensive ex vivo and in vivo studies are required to put the Raman spectroscopy technology into clinical practice.