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拉曼光谱技术在肿瘤诊断上的应用研究进展 (封面文章)

Research Progress on Application of Raman Spectroscopy in Tumor Diagnosis (Cover Paper)

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摘要

肿瘤是一种严重威胁我国居民生命健康的重大疾病。现有的肿瘤诊断方式存在诊断时间长、创伤严重和误判率高等问题,且严重依赖于医生的主观经验。因此,研究出具有智能属性的肿瘤诊断技术对于提升我国的肿瘤诊断水平具有重要意义。拉曼光谱技术是一种无需标记的光学技术,在肿瘤的良恶性判别、肿瘤的亚型分类、切片病理诊断、原位近实时成像等方面被广泛应用。此外,人们将拉曼光谱与人工智能结合发展了具有智能属性的诊断方式。本文主要综述了近三年拉曼光谱技术在各种类型肿瘤诊断上的研究进展,主要从常规拉曼光谱诊断、拉曼成像诊断与探头结合光谱诊断三方面展开介绍,并对拉曼光谱技术在肿瘤诊断中的应用前景进行了展望。

Abstract

Tumors are a major disease that seriously threaten the life and health of Chinese residents. Existing tumor diagnosis methods heavily rely on the subjective experience of doctors and include many issues, such as prolonged diagnosis, severe trauma, and high misdiagnosis rate. Therefore, it is crucial to develop a tumor diagnosis technology with intelligent properties to improve the level of diagnosing tumors in China. Raman spectroscopy is a label-free optical technique used for diagnosing benign and malignant tumors, classifying tumor subtypes, pathological diagnosis of biopsy, and in situ near-real-time imaging. Moreover, Raman spectroscopy combined with artificial intelligence has led to an intelligent diagnostic method. In this paper, the research progress of Raman spectroscopy for diagnosing various tumor types over the past three years was reviewed. Furthermore, three main aspects of the conventional Raman spectrum, Raman imaging, and probe diagnoses combined with the spectrum were introduced, and the prospect of Raman spectroscopy in the diagnosis of tumors in the future was discussed.

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中图分类号:O657.37

DOI:10.3788/LOP57.220001

所属栏目:综述

基金项目:国家自然科学基金;

收稿日期:2020-07-13

修改稿日期:2020-08-07

网络出版日期:2020-11-01

作者单位    点击查看

祁亚峰:清华大学机械工程系摩擦学国家重点实验室, 北京 100084
刘宇宏:清华大学机械工程系摩擦学国家重点实验室, 北京 100084
刘大猛:清华大学机械工程系摩擦学国家重点实验室, 北京 100084

联系人作者:刘宇宏(liuyuhong@tsinghua.edu.cn)

备注:国家自然科学基金;

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引用该论文

Qi Yafeng,Liu Yuhong,Liu Dameng. Research Progress on Application of Raman Spectroscopy in Tumor Diagnosis[J]. Laser & Optoelectronics Progress, 2020, 57(22): 220001

祁亚峰,刘宇宏,刘大猛. 拉曼光谱技术在肿瘤诊断上的应用研究进展[J]. 激光与光电子学进展, 2020, 57(22): 220001

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