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    • 12. 发明申请
    • Cytological methods for detecting a disease condition such as malignancy by Raman spectroscopic imaging
    • 通过拉曼光谱成像检测恶性肿瘤的疾病状况的细胞学方法
    • US20060281068A1
    • 2006-12-14
    • US11269596
    • 2005-11-09
    • John MaierShona StewartPatrick Treado
    • John MaierShona StewartPatrick Treado
    • C12Q1/00C12Q1/70C12Q1/68G06F19/00G01J3/44
    • G01N21/65G01N2021/656
    • Raman molecular imaging (RMI) is used to detect mammalian cells of a particular phenotype. For example the disclosure includes the use of RMI to differentiate between normal and diseased cells or tissues, e.g., cancer cells as well as in determining the grade of said cancer cells. In a preferred embodiment benign and malignant lesions of bladder and other tissues can be distinguished, including epithelial tissues such as lung, prostate, kidney, breast, and colon, and non-epithelial tissues, such as bone marrow and brain. Raman scattering data relevant to the disease state of cells or tissue can be combined with visual image data to produce hybrid images which depict both a magnified view of the cellular structures and information relating to the disease state of the individual cells in the field of view. Also, RMI techniques may be combined with visual image data and validated with other detection methods to produce confirm the matter obtained by RMI.
    • 拉曼分子成像(RMI)用于检测特定表型的哺乳动物细胞。 例如,本公开包括使用RMI来区分正常和患病细胞或组织,例如癌细胞,以及确定所述癌细胞的等级。 在一个优选实施方案中,可以区分膀胱和其他组织的良性和恶性病变,包括上皮组织如肺,前列腺,肾,乳腺和结肠以及非上皮组织,例如骨髓和脑。 可以将与细胞或组织的疾病状态相关的拉曼散射数据与视觉图像数据组合,以产生描绘细胞结构的放大视图和与视野中的各个细胞的疾病状态有关的信息的混合图像。 此外,RMI技术可以与可视图像数据组合,并用其他检测方法验证,以确定RMI获得的事项。
    • 18. 发明授权
    • System and method for classifying cells and the pharmaceutical treatment of such cells using Raman spectroscopy
    • 使用拉曼光谱分析细胞的系统和方法以及这种细胞的药物处理
    • US07570356B2
    • 2009-08-04
    • US11650378
    • 2007-01-05
    • Janice L. PanzaJohn MaierJason Neiss
    • Janice L. PanzaJohn MaierJason Neiss
    • G01J3/44G01J3/00
    • G01J3/44G01J3/28G01J3/36G01N15/1475G01N21/65G01N2015/1006G01N2015/1488G01N2021/656
    • A system and method to distinguish normal cells from apoptotic cells. A pre-determined vector space is selected where the vector space mathematically describes a first plurality of reference Raman data sets for normal cells and a second plurality of reference Raman data sets for apoptotic cells. A sample is irradiated with substantially monochromatic light generating a target Raman data set based on scattered photons. The target Raman data set is transformed into a vector space defined by the pre-determined vector space. A distribution of transformed data is analyzed in the pre-determined vector space. Based on the analysis, the sample is classified as containing normal cells, apoptotic cells, and a combination of normal and apoptotic cells. The sample includes the step of treating the sample with a pharmaceutical agent prior to irradiating the sample. Based on the classification, the therapeutic efficiency of the pharmaceutical agent is assessed.
    • 将正常细胞与凋亡细胞区分开的系统和方法。 选择预定矢量空间,其中矢量空间在数学上描述用于正常细胞的第一多个参考拉曼数据集和用于凋亡细胞的第二多个参考拉曼数据集。 用基本上单色的光照射样品,产生基于散射光子的目标拉曼数据集。 目标拉曼数据集被转换成由预定向量空间定义的向量空间。 在预定向量空间中分析变换数据的分布。 基于分析,样品被分类为含有正常细胞,凋亡细胞,以及正常细胞和凋亡细胞的组合。 样品包括在照射样品之前用药剂处理样品的步骤。 根据分类,评估药剂的治疗效果。