• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用于脑肿瘤分析的非线性显微镜、红外和拉曼微光谱学。

Nonlinear microscopy, infrared, and Raman microspectroscopy for brain tumor analysis.

机构信息

Institute of Photonic Technology e.V., Albert-Einstein-Strasse 9, 07745 Jena, Germany.

出版信息

J Biomed Opt. 2011 Feb;16(2):021113. doi: 10.1117/1.3533268.

DOI:10.1117/1.3533268
PMID:21361676
Abstract

Contemporary brain tumor research focuses on two challenges: First, tumor typing and grading by analyzing excised tissue is of utmost importance for choosing a therapy. Second, for prognostication the tumor has to be removed as completely as possible. Nowadays, histopathology of excised tissue using haematoxylin-eosine staining is the gold standard for the definitive diagnosis of surgical pathology specimens. However, it is neither applicable in vivo, nor does it allow for precise tumor typing in those cases when only nonrepresentative specimens are procured. Infrared and Raman spectroscopy allow for very precise cancer analysis due to their molecular specificity, while nonlinear microscopy is a suitable tool for rapid imaging of large tissue sections. Here, unstained samples from the brain of a domestic pig have been investigated by a multimodal nonlinear imaging approach combining coherent anti-Stokes Raman scattering, second harmonic generation, and two photon excited fluorescence microscopy. Furthermore, a brain tumor specimen was additionally analyzed by linear Raman and Fourier transform infrared imaging for a detailed assessment of the tissue types that is required for classification and to validate the multimodal imaging approach. Hence label-free vibrational microspectroscopic imaging is a promising tool for fast and precise in vivo diagnostics of brain tumors.

摘要

当代脑肿瘤研究主要集中在两个挑战上

首先,通过分析切除的组织对肿瘤进行分类和分级,对于选择治疗方法至关重要。其次,为了进行预后评估,必须尽可能完全切除肿瘤。目前,使用苏木精-伊红染色对切除的组织进行组织病理学检查是手术病理标本明确诊断的金标准。然而,它既不适用于体内,也不能在仅获得非代表性标本的情况下进行精确的肿瘤分类。由于具有分子特异性,红外和拉曼光谱可非常精确地进行癌症分析,而非线性显微镜则是快速成像大组织切片的合适工具。在这里,我们通过结合相干反斯托克斯拉曼散射、二次谐波产生和双光子激发荧光显微镜的多模态非线性成像方法,对来自家猪大脑的未经染色的样本进行了研究。此外,还通过线性拉曼和傅里叶变换红外成像对脑肿瘤标本进行了分析,以详细评估组织类型,这是分类所必需的,并验证了多模态成像方法。因此,无标记振动显微光谱成像技术是一种快速、精确的脑肿瘤体内诊断的有前途的工具。

相似文献

1
Nonlinear microscopy, infrared, and Raman microspectroscopy for brain tumor analysis.用于脑肿瘤分析的非线性显微镜、红外和拉曼微光谱学。
J Biomed Opt. 2011 Feb;16(2):021113. doi: 10.1117/1.3533268.
2
Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing.提高非线性拉曼微光谱成像和传感的灵敏度。
J Biomed Opt. 2011 Feb;16(2):021114. doi: 10.1117/1.3533317.
3
Label-free imaging and quantitative chemical analysis of Alzheimer's disease brain samples with multimodal multiphoton nonlinear optical microspectroscopy.利用多模态多光子非线性光学显微光谱技术对阿尔茨海默病脑样本进行无标记成像和定量化学分析。
J Biomed Opt. 2015 May;20(5):56013. doi: 10.1117/1.JBO.20.5.056013.
4
Adaptive optics for enhanced signal in CARS microscopy.用于增强相干反斯托克斯拉曼散射显微镜信号的自适应光学技术。
Opt Express. 2007 Dec 24;15(26):18209-19. doi: 10.1364/oe.15.018209.
5
Coherent anti-stokes raman scattering spectral interferometry: determination of the real and imaginary components of nonlinear susceptibility chi(3) for vibrational microscopy.相干反斯托克斯拉曼散射光谱干涉术:用于振动显微镜的非线性极化率χ(3)实部和虚部的测定
Opt Lett. 2004 Dec 15;29(24):2923-5. doi: 10.1364/ol.29.002923.
6
Coherent anti-Stokes Raman scattering and two photon excited fluorescence for neurosurgery.用于神经外科手术的相干反斯托克斯拉曼散射和双光子激发荧光
Clin Neurol Neurosurg. 2015 Apr;131:42-6. doi: 10.1016/j.clineuro.2015.01.022. Epub 2015 Jan 31.
7
Forward-collected simultaneous fluorescence lifetime imaging and coherent anti-Stokes Raman scattering microscopy.正向采集的荧光寿命成像和相干反斯托克斯拉曼散射显微镜。
J Biomed Opt. 2011 Feb;16(2):021103. doi: 10.1117/1.3490641.
8
Comparison of the sensitivity and image contrast in spontaneous Raman and coherent Stokes Raman scattering microscopy of geometry-controlled samples.几何结构可控样品的自发拉曼和相干斯托克斯拉曼散射显微镜的灵敏度和图像对比度比较。
J Biomed Opt. 2011 Feb;16(2):021107. doi: 10.1117/1.3533310.
9
Label-free tetra-modal molecular imaging of living cells with CARS, SHG, THG and TSFG (coherent anti-Stokes Raman scattering, second harmonic generation, third harmonic generation and third-order sum frequency generation).利用相干反斯托克斯拉曼散射(CARS)、二次谐波产生(SHG)、三次谐波产生(THG)和三阶和频产生(TSFG)对活细胞进行无标记四模态分子成像。
Opt Express. 2012 Apr 23;20(9):9551-7. doi: 10.1364/OE.20.009551.
10
Label-free imaging of biomolecules in food products using stimulated Raman microscopy.利用受激拉曼显微镜对食品中的生物分子进行无标记成像。
J Biomed Opt. 2011 Feb;16(2):021118.

引用本文的文献

1
Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer.拉曼光谱法:一种用于脑癌分子指纹识别的工具。
ACS Omega. 2023 Jul 27;8(31):27845-27861. doi: 10.1021/acsomega.3c01848. eCollection 2023 Aug 8.
2
From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives.从拉曼光谱在神经科学中的研究到诊断应用:过去与展望
Free Neuropathol. 2022 Aug 5;3:19. doi: 10.17879/freeneuropathology-2022-4210. eCollection 2022 Jan.
3
Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review.
利用拉曼和红外光谱技术进行分子指纹检测在癌症检测中的应用:进展综述。
Biosensors (Basel). 2023 May 18;13(5):557. doi: 10.3390/bios13050557.
4
Viewing life without labels under optical microscopes.在光学显微镜下观察无标签的生命。
Commun Biol. 2023 May 25;6(1):559. doi: 10.1038/s42003-023-04934-8.
5
Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury.综述:创伤性脑损伤的新兴眼部诊断技术。
IEEE Rev Biomed Eng. 2023;16:530-559. doi: 10.1109/RBME.2022.3161352. Epub 2023 Jan 5.
6
Orthogonally-polarized excitation for improved two-photon and second-harmonic-generation microscopy, applied to neurotransmitter imaging with GPCR-based sensors.用于改进双光子和二次谐波产生显微镜的正交偏振激发,应用于基于G蛋白偶联受体(GPCR)传感器的神经递质成像。
Biomed Opt Express. 2022 Jan 14;13(2):777-790. doi: 10.1364/BOE.448760. eCollection 2022 Feb 1.
7
Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning.使用监督式和非监督式深度学习对非线性多模态成像进行计算组织染色。
Biomed Opt Express. 2021 Mar 23;12(4):2280-2298. doi: 10.1364/BOE.415962. eCollection 2021 Apr 1.
8
Glioma Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples.基于新鲜组织样本利用拉曼光谱和机器学习模型进行胶质瘤分类
Cancers (Basel). 2021 Mar 3;13(5):1073. doi: 10.3390/cancers13051073.
9
Feasibility evaluation of micro-optical coherence tomography (μOCT) for rapid brain tumor type and grade discriminations: μOCT images versus pathology.微光学相干断层扫描(μOCT)在快速脑肿瘤类型和分级鉴别中的可行性评估:μOCT 图像与病理学比较。
BMC Med Imaging. 2019 Dec 30;19(1):102. doi: 10.1186/s12880-019-0405-6.
10
Portable all-fiber dual-output widely tunable light source for coherent Raman imaging.用于相干拉曼成像的便携式全光纤双输出宽可调谐光源。
Biomed Opt Express. 2019 Aug 5;10(9):4437-4449. doi: 10.1364/BOE.10.004437. eCollection 2019 Sep 1.