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北京大学学报（医学版） ›› 2022, Vol. 54 ›› Issue (4): 779-784. doi: 10.19723/j.issn.1671-167X.2022.04.033

• 综述 • 上一篇    

拉曼技术在泌尿系统肿瘤检测中的应用

郝哲1,岳蜀华*(),周利群*()   

  1. 1. 北京航空航天大学生物与医学工程学院，北京市生物医学工程高精尖创新中心，生物力学与力生物学教育部重点实验室，医用光子学研究所，北京 100083
    2. 北京大学第一医院泌尿外科，北京大学泌尿外科研究所，国家泌尿、男性生殖系肿瘤研究中心，泌尿生殖系疾病(男)分子诊治北京市重点实验室，北京 100034
  • 收稿日期:2022-04-06 出版日期:2022-08-18 发布日期:2022-08-11
  • 通讯作者: 岳蜀华,周利群 E-mail:yue_shuhua@buaa.edu.cn;zhoulqmail@sina.com
  • 基金资助:
    国家自然科学基金(62027824);首都卫生发展科研专项(2020-2Z-40713);首都卫生发展科研专项(2022-1-4072);首都临床诊疗技术特色研究及转化应用重点项目(Z211100002921070);北大百度基金(2020BD033)

Application of Raman-based technologies in the detection of urological tumors

Zhe HAO1,Shu-hua YUE*(),Li-qun ZHOU*()   

  1. 1. School of Biological and Medical Engineering, Beihang University, Beijing Advanced Innovation Center for Biomedical Engineering, Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing 100083, China
    2. Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; National Urological Cancer Center; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, Beijing 100034, China
  • Received:2022-04-06 Online:2022-08-18 Published:2022-08-11
  • Contact: Shu-hua YUE,Li-qun ZHOU E-mail:yue_shuhua@buaa.edu.cn;zhoulqmail@sina.com
  • Supported by:
    National Natural Science Foundation of China(62027824);Capital Health Research and Development of Special(2020-2Z-40713);Capital Health Research and Development of Special(2022-1-4072);Clinical Features Research of Capital(Z211100002921070);Peking University Baidu Fund Grant(2020BD033)

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关键词: 泌尿系肿瘤, 诊断, 光谱分析, 拉曼

Abstract:

Urinary system tumors affect a huge number of individuals, and are frequently recurrent and progressing following surgery, necessitating lifelong surveillance. As a result, early and precise diagnosis of urinary system cancers is important for prevention and therapy. Histopathology is now the golden stan-dard for the diagnosis, but it is invasive, time-consuming, and inconvenient for initial diagnosis and re-gular follow-up assessment. Endoscopy can directly witness the tumor's structure, but intrusive detection is likely to cause harm to the patient's organs, and it is apt to create other hazards in frequently examined patients. Imaging is a valuable non-invasive and quick assessment tool; however, it can be difficult to define the type of lesions and has limited sensitivity for early tumor detection. The conventional approaches for detecting tumors have their own set of limitations. Thus, detection methods that combine non-invasive detection, label-free detection, high sensitivity and high specificity are urgently needed to aid clinical diagnosis. Optical diagnostics and imaging are increasingly being employed in healthcare settings in a variety of sectors. Raman scattering can assess changes in molecular signatures in cancer cells or tissues based on the interaction with vibrational modes of common molecular bonds. Due to the advantages of label-free, strong chemical selectivity, and high sensitivity, Raman scattering, especially coherent Raman scattering microscopy imaging with high spatial resolution, has been widely used in biomedical research. And quantity studies have shown that it has a good application in the detection and diagnosis of bladder can-cer, renal clear cell carcinoma, prostate cancer, and other cancers. In this paper, several nonlinear imaging techniques based on Raman scattering technology are briefly described, including Raman spectroscopy, coherent anti-Stokes Raman scattering, stimulated Raman scattering, and surface-enhanced Raman spectroscopy. And we will discuss the application of these techniques for detecting urologic malignancy. Future research directions are predicted using the advantages and limitations of the aforesaid methodologies in the research. For clinical practice, Raman scattering technology is intended to enable more accurate, rapid, and non-invasive in early diagnosis, intraoperative margins, and pathological grading basis for clinical practice.

Key words: Urologic neoplasms, Diagnosis, Spectrum analysis, Raman

中图分类号: 

  • R737.1
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