Department of Nephrology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan, 430081, China.
Adv Sci (Weinh). 2024 Feb;11(7):e2300668. doi: 10.1002/advs.202300668. Epub 2023 Dec 10.
Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed.
早期临床诊断、有效的术中指导和准确的预后可以实现及时有效的医疗。目前常规的临床方法存在一些局限性。因此,需要开发更快、更可靠的临床检测、治疗和监测方法,以增强其临床应用。拉曼光谱是非侵入性的,可以快速准确地提供有关分析物的分子结构和生化组成的高度特异性信息。它在生物医学、材料和临床环境中有广泛的应用。本综述主要关注拉曼光谱在临床医学中的应用。讨论了拉曼光谱相对于传统临床方法的优势和局限性。此外,还展示了将拉曼光谱与机器学习、纳米粒子和探针结合的优势,从而将其应用扩展到不同的临床阶段。还整合了过去 3 年拉曼光谱在临床医学中的应用实例。最后,调查了基于拉曼光谱在临床研究中的各种前瞻性方法,并讨论了当前的挑战。