化学计量学
边距(机器学习)
范围(计算机科学)
计算机科学
医学物理学
光谱学
癌症治疗
癌症检测
分光计
领域(数学)
数据科学
医学
癌症
光学
机器学习
数学
物理
内科学
程序设计语言
纯数学
量子力学
作者
Ekaterina Boichenko,Dmitry Kirsanov
标识
DOI:10.1016/j.trac.2023.116955
摘要
Spectroscopic techniques developed in analytical chemistry have become an important part of medical and biological research. Optical spectroscopy is widely used in research devoted to cancer diagnosis, therapy, and surgery. The lack of an efficient and cost-effective method for real-time assessment of tumor margins leads to high rates of re-excision surgeries and overloading of medical facilities. Rapid spectra acquisition, a wide range of commercially available spectrometers and fiber optics, and minimal invasiveness underlie the application of optical spectroscopy for intraoperative margins detection. Since the number of published papers in this field is growing, it is worth summarizing current achievements and perspectives of further development. Combinations “spectroscopic technique” + “cancer type” + “method of data analysis” are truly numerous, it is important to know what has been done in this field and what is yet to come. In this review, we discuss key points in the development of a spectroscopic tool for intraoperative margins assessment (IMA), based on the analysis of spectral data (imaging techniques are beyond the scope of this work). Specific attention will be paid to experimental designs and results of chemometric data analysis.
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