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拉曼光谱技术在脑胶质瘤检测中的应用研究

葛梅兰 王与烨 李海滨 徐德刚 姚建铨

葛梅兰, 王与烨, 李海滨, 徐德刚, 姚建铨. 拉曼光谱技术在脑胶质瘤检测中的应用研究[J]. 中国光学(中英文), 2024, 17(5): 995-1013. doi: 10.37188/CO.2024-0003
引用本文: 葛梅兰, 王与烨, 李海滨, 徐德刚, 姚建铨. 拉曼光谱技术在脑胶质瘤检测中的应用研究[J]. 中国光学(中英文), 2024, 17(5): 995-1013. doi: 10.37188/CO.2024-0003
GE Mei-lan, WANG Yu-ye, LI Hai-bin, XU De-gang, YAO Jian-quan. Application of Raman spectroscopy in the detection of brain glioma[J]. Chinese Optics, 2024, 17(5): 995-1013. doi: 10.37188/CO.2024-0003
Citation: GE Mei-lan, WANG Yu-ye, LI Hai-bin, XU De-gang, YAO Jian-quan. Application of Raman spectroscopy in the detection of brain glioma[J]. Chinese Optics, 2024, 17(5): 995-1013. doi: 10.37188/CO.2024-0003

拉曼光谱技术在脑胶质瘤检测中的应用研究

基金项目: 国家自然科学基金(No. 62175182,No. U22A20353,No. 62275193,No. U22A20123)
详细信息
    作者简介:

    葛梅兰(1991—),女,陕西宝鸡人,博士,主要研究方向为太赫兹-拉曼光谱技术及其在生物医学中的应用研究。E-mail:meilange@tju.edu.cn

    王与烨(1983—),女,山西朔州人,教授,博士生导师,2009年于天津大学获得博士学位,主要研究方向为太赫兹光子学辐射源技术及其应用。E-mail:yuyewang@tju.edu.cn

    李海滨(1998—),女,河北保定人,博士研究生,2020年于长春理工大学获得学士学位,主要研究方向为太赫兹生物医学成像研究。E-mail:haibin_li@tju.edu.cn

    徐德刚(1974—),男,山东青岛人,教授,博士生导师,2005年于天津大学获得博士学位,主要研究方向为激光与光电子技术、太赫兹技术及激光雷达等。E-mail:xudegang@tju.edu.cn

    姚建铨(1939—),男,上海人,中国科学院院士,1957年毕业于天津大学精仪系,著名激光与非线性光学专家。E-mail:jqyao@tju.edu.cn

  • 中图分类号: TN29

Application of Raman spectroscopy in the detection of brain glioma

Funds: Supported by the National Natural Science Foundation of China (No. 62175182, No. U22A20353, No. 62275193, No. U22A20123)
More Information
  • 摘要:

    脑胶质瘤是一种常见的颅内原发性肿瘤,具有治愈率低、复发率高等特点。脑胶质瘤边界的精准识别是减少患者术后复发、改善愈后状况的重要前提。因此,发展快速、高灵敏度、无标记的脑胶质瘤诊断方法具有重要的临床意义。拉曼光谱技术作为一种指纹谱,能够在分子水平上反映物质的化学和结构信息,已经在脑胶质瘤的定性定位识别中表现出巨大的应用前景。本文首先介绍了不同种类的拉曼光谱技术,其次梳理了拉曼光谱技术在脑胶质瘤中的研究现状,最后对拉曼光谱技术在脑胶质瘤检测中的未来发展进行展望。

     

  • 图 1  Raman光谱在脑胶质瘤检测中的研究现状

    Figure 1.  The research state of the application of Raman spectroscopy in the detection of brain glioma

    图 12  正常组织和不同恶性胶质瘤组织中(a)1588 cm−11440 cm−1和(b)2934 cm−12885 cm−1 Raman强度比值,其中G0-N为正常脑组织;GI:I级胶质瘤;GII:II级胶质瘤;GIII:III级胶质瘤;GIV:IV级胶质瘤[45]

    Figure 12.  The ratios of (a) I1588 cm−1I1440 cm−1 and (b) I2934 cm−1 ∕I2885 cm−1 from normal human brain tissues and glioma tissues with increasing malignancy; G0-N: normal human brain tissues; GI: grade I; GII: grade II; GIII: grade III; GIV: grade IV[45]

    图 13  正常、低级别胶质瘤样本(I&II)与高级别胶质瘤样本(III&IV)的聚类结果[45]

    Figure 13.  The clustering results of normal tissue, low-grade (I and II) , and high-grade (III and IV) glioma[45]

    图 14  健康小鼠大脑的CARS显微图像[46]

    Figure 14.  CARS microscopy image of a healthy mouse brain[46]

    图 15  (a)为图14中白色框中的放大图像;(b)为(a)中对应位置处的H&E图像[46]

    Figure 15.  (a) The enlarged image of the white rectangle in the Fig. 14; (b) H&E image of the same region in Fig. 15(a)[46]

    图 16  小鼠脑中星形细胞瘤的CARS图像。(a)低分辨率、大视场的CARS显微镜图像;(b)为(a)图中矩形区域局部组织的CARS图像[46]

    Figure 16.  CARS images of astrocytoma in mouse’s brain. (a) Mosaic CARS microscopy image with low-resolution and large field of view; (b) the CARS image of local tissue of the white rectangle in (a) [46]

    图 17  (a)小鼠脑胶质母细胞瘤的明场图像,其中黑色线为肿瘤边界,青色为感兴趣区域;(b)感光趣区域内的显微图像;(c)肿瘤和正常脑组织的伪彩色图像,蓝色为细胞核、红色为脂质含量、绿色为红细胞;(d)利用细胞核(蓝色)、脂质含量(红色)绘制的CARS图像;(e)细胞核(蓝色)、脂质含量(红色)、CH3-CH2拉伸(绿色)绘制的CARS图像,NB为正常脑组织,T为肿瘤细胞,WM为白质;(f)肿瘤、白质和正常组织的CARS光谱[47]

    Figure 17.  (a) Bright field image of glioblastoma in mouse brain, with the tumor boundary outlined (black). The cyan indicates a region of interest (ROI); (b) micrograph of ROIs; (c) pseudocolour CARS image of tumor and normal brain tissues, with nuclei highlighted in blue, lipid content in red and red blood cells in green; (d) CARS image with nuclei highlighted in blue and lipid content in red; (e) CARS image with nuclei highlighted in blue, lipid content in red and CH3 stretch–CH2 in green, NB: normal brain; T: tumor cells, WM: white matter; (f) normalized CARS of different tissues[47]

    图 18  新鲜小鼠组织的SRS图像。(a)特征峰2845 cm−1处小鼠脑胼胝体神经元束中标记出髓鞘中含丰富CH2;(b)约1 mm厚脑组织切片CH2的SRS图像;(c)3个独立区域在同一深度处,小鼠耳皮肤中CH2的SRS图像。从左到右依次为:角质层、皮脂腺和皮下脂肪层;(d)角质层有无CH2共振的SRS和CARS图像对比[47]

    Figure 18.  SRS imaging of fresh mouse tissue. (a) The myelin sheath neuron bundles of the corpus callosum in mouse brain is marked with abundant CH2 at the characteristic peak of 2845 cm−1; (b) SRS image of CH2 acquired from a brain tissue slice ~1 mm thick; (c) SRS images of CH2 in three separate regions at the same depth in mouse ear skin. From left to right: stratum corneum, sebaceous gland, and subcutaneous fat layer; (d) comparison of SRS and CARS images of stratum corneum on and off the CH2 resonance[47]

    图 19  (a)健康、(b)II级、(c)III级、(d)IV级胶质瘤组织不同位置的SERS光谱[50]

    Figure 19.  SERS spectra of (a) healthily, (b) II grade, (c) III grade, (d) IV grade tissue[50]

    图 6  文献[42]的(a)拉曼检测系统示意图及(b)小鼠用于在体拉曼检测的图片[42]

    Figure 6.  (a) Schematic diagram of the Raman system in Ref. [42] and (b) photo of Raman measurement based on mouse model in vivo[42]

    图 7  (a)皮层暴露后小鼠脑组织;(b)通过聚类分割后的Raman图像。其中,蓝色、青色和黄色为正常组织,红色为血管,灰色为肿瘤组织,黑色为肿瘤边缘;(c)组织的显微照片和Raman图像的叠加[42]

    Figure 7.  (a) Mouse brain tissue with exposed cortex; (b) Raman images are segmented by cluster analysis. Normal brain tissue is depicted in blue, cyan, and yellow, the red is blood vessel, and the tumor and tumor margin are shown in gray and black, respectively; (c) superimposition of the photomicrograph and the Raman image of the tissue[42]

    图 8  手持接触式Raman光谱探针的(a)实验系统示意图及(b)基于探针的脑组织检测图[43]

    Figure 8.  (a) Schematic diagram of experimental setup of the handheld contact Raman spectroscopy probe for and (b) photo of brain tissue detection based on the probe[43]

    图 9  (a)商用活检针内部的拉曼微探针组件的分解图;(b)拉曼检测的神经导航系统图[43]

    Figure 9.  (a) Exploded view of the Raman microprobe components along the internal cannula of the commercial brain biopsy needle; (b) images from the neuronavigation system in the process of Raman detection[43]

    图 10  手持式接触探针在不同组织处的Raman结果。(a)胶质瘤切除术期间,使用手持式接触探针定位致密肿瘤组织(红色)、浸润性组织(黄色)和周围正常组织位置图;(b)在体致密性肿瘤组织、浸润性组织和正常组织的高波数Raman光谱,(c)每种类型组织的H&E染色显微图片[44]

    Figure 10.  The Raman results of handheld contact probes at different tissue locations. (a) Schematic diagram of in vivo Raman spectral measurements taken in the surgical cavity during glioma resection, using a handheld contact probe to target dense cancerous tissue (red), infiltrated brain tissue (yellow) and surrounding normal brain tissue; (b) In vivo high wavenumber Raman spectra of dense cancer, infiltrated brain and normal brain, averaged over all samples; (c) Representative H&E-stained micrographs for each tissue type[44]

    图 11  使用SVM算法对正常组织、浸润组织和致密性肿瘤组织的识别结果。(a)脑胶质瘤患者中,正常脑组织、浸润脑组织和致密型肿瘤脑组织中脂质和蛋白的Raman强度比值(2930 cm−12845 cm−1)的箱线图;(b)基于SVM算法的受试者特性曲线[44]

    Figure 11.  The identification results of normal brain, infiltrated brain and dense cancer tissue based on SVM algorithm. (a) Boxplots of the Raman intensity ratio of the lipid and protein in the bands of 2930 cm−1:2845 cm−1 for normal brain, infiltrated brain and dense cancer tissue in glioma patients; (b) receiver operating characteristic curve computed by the SVM algorithm[44]

    图 2  (a)和(b)为未染色人胶质母细胞瘤冰冻切片在显微镜下的照片;(c)和(d)为Raman光谱绘制的组织切片的伪彩色图(分别对应于(a)和(b))。红色:主要的肿瘤组织区域,蓝色:坏死组织;黄色:未显示区域(边缘冷冻样品);(e)和(f)为H&E染色后照片;(g)为(f)图中绿框处放大后的图片[34]

    Figure 2.  (a) and (b) are photomicrographs of unstained human glioblastoma cryosections used in Raman mapping experiments; (c) and (d) are pseudo-color maps of Raman spectra of the tissue sections shown in (a) and (b). Red: areas of vital tumor tissue; blue: areas of necrosis; yellow: areas in the scan where no tissue was present (edges, freezing artifacts); (e) and (f) are photomicrographs of the same tissue sections after H&E staining; (g) ×40 magnification of detail marked with a green frame in (f)[34]

    图 3  浸润性组织不同成分的(a)Raman光谱及(b)拉曼成像结果[36]

    Figure 3.  (a) Raman spectra and (b) Raman imaging results of different components in invasive tissue[36]

    图 4  IDH1突变型(IDH1-mut)和野生型(IDH1-wt)的Raman光谱对比[39]

    Figure 4.  Comparison of Raman spectra of IDH1-wt and IDH1-mut glioma[39]

    图 5  健康(蓝色)和胶质瘤组织(红色)的平均Raman光谱[39]

    Figure 5.  The average Raman spectra of healthy (blue) and tumorous tissue (red)[39]

    图 20  神经胶质瘤细胞和正常星形胶质细胞中的(a)Raman光谱测量结果和(b)Raman光谱之间的差异[50]

    Figure 20.  (a) Measurement results of Raman scattering spectra and (b) the difference in Raman spectra between neuronal glioma cells and normal astrocytes[50]

    图 21  C6和SK-N-SH细胞系分化、未分化和正常神经细胞的Raman光谱[52]

    Figure 21.  Raman spectra of differentiated, undifferentiated C6 and SK-N-SH cells and normal neuronal cells[52]

    图 22  分化(红色)和未分化(黑色)细胞的Raman特征峰的强度差异[52]

    Figure 22.  Difference in marker peak intensities for differentiated and undifferentiated cells. (a) C6 cells; (b) SK-N-SH cells[52]

    表  1  3种非线性拉曼光谱技术CARS、SRS和SERS的优缺点对比

    Table  1.   Comparison of advantages and disadvantages of the three nonlinear Raman spectroscopy techniques: CARS, SRS and SERS

    拉曼光谱
    技术
    CARSSRSSERS
    优点无标记无标记、
    标准谱
    克服荧光背景噪声
    缺点易受非共振背景噪声影响、非标准谱、系统复杂系统复杂、分子选择性强引入新的金属材料、基底制备工艺复杂
    下载: 导出CSV

    表  2  不同拉曼光谱技术在脑胶质瘤生物标志物中的应用

    Table  2.   Application of different Raman spectroscopy techniques in the detection of brain glioma biomarkers

    年份 拉曼技术 标志物 光谱范围/cm−1 参考文献
    2021 表面增强拉曼 循环肿瘤DNA 100~1800 [71]
    2023 表面增强拉曼 血管内皮生成因子 200~1800 [54]
    2018 共振拉曼光谱 乳酸和三磷脂酸腺苷 500~4000 [72]
    2023 共聚焦拉曼光谱 糖基化 400~1800 [73]
    2023 自发拉曼光谱 γ-氨基丁酸 0~150 [74]
    下载: 导出CSV
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  • 收稿日期:  2024-01-02
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