Label-free brain tumor imaging using Raman-based methods.
Label-free brain tumor imaging using Raman-based methods.
复制标题
使用基于拉曼的方法的无标记脑肿瘤成像。
DOI：
10.1007/s11060-019-03380-z
复制
发表时间：
2021-03
影响因子：
3.9
通讯作者：
Orringer, Daniel A.
中科院分区：
文献类型：
--
作者：
Hollon, Todd;Orringer, Daniel A.
关键词：
无标记拉曼成像技术为将化学和组织学数据带入手术室创造了可能性。依靠组织的固有生化特性来产生图像对比度和光学组织切片，基于拉曼的成像方法可用于检测微观肿瘤浸润和诊断脑肿瘤亚型。本文综述了三种基于拉曼的成像方法在神经外科肿瘤学中的应用：拉曼光谱、相干反斯托克斯拉曼散射（汽车）显微镜和受激拉曼组织学（SRH）。拉曼光谱允许组织的化学表征，并且可以基于离体和体内的大分子含量的变化来区分正常和肿瘤浸润的组织。为了与常规拉曼光谱相比提高信噪比，可以使用第二脉冲激发激光器来相干地驱动特定拉曼活性化学键（即-CH 2键的对称拉伸）的振动频率。相干拉曼成像，包括汽车和受激拉曼散射显微镜，已被证明可以用亚微米图像分辨率检测新鲜脑肿瘤标本中的显微脑肿瘤浸润。光纤激光技术的进步使得术中SRH以及人工智能算法的发展成为可能，以促进SRH图像的解释。随着分子诊断成为脑肿瘤分类的重要组成部分，初步研究表明，基于拉曼光谱的方法可用于术中诊断胶质瘤分子类别。这些结果证明了无标记的基于拉曼的成像方法如何可以用于通过检测肿瘤浸润、引导肿瘤活检/切除以及提供用于组织病理学和分子诊断的图像来改善脑肿瘤患者的治疗。
Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes. Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spec- troscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH). Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of –CH2 bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the develop- ment of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively. These results demonstrate how label-free Raman-based imaging methods can be used to improve the man- agement of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.
登录
查看更多内容
影响因子：
4.1
作者：
Lau, Darryl;Hervey-Jumper, Shawn L.;Berger, Mitchel S.
通讯作者：
Berger, Mitchel S.
影响因子：
2.8
作者：
Galli, Roberta;Uckermann, Ortrud;Kirsch, Matthias
通讯作者：
Kirsch, Matthias
影响因子：
3.4
作者：
Jermyn, Michael;Desroches, Joannie;Petrecca, Kevin
通讯作者：
Petrecca, Kevin
影响因子：
35
作者：
通讯作者：
--
影响因子：
4.3
作者：
Kirsch, Matthias;Schackert, Gabriele;Krafft, Christoph
通讯作者：
Krafft, Christoph