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用高分辨魔角旋转核磁共振氢谱技术结合模式识别方法对人类神经上皮肿瘤进行分级

, PP. 532-543

Keywords: 神经上皮肿瘤,分级,高分辨魔角旋转核磁共振氢谱,代谢组学,模式识别

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Abstract:

临床资料显示,患有脑肿瘤病人的存活率通常与肿瘤的类型和级别有关.如通过高分辨魔角旋转核磁共振氢谱(HRMAS1HNMRS)技术检测得到肿瘤组织的代谢轮廓(特征),不仅可为肿瘤的生物学和新陈代谢研究提供有价值的信息,而且可为肿瘤的分类和分级提供重要的代谢指纹特征,而这些特征有可能成为未来肿瘤诊断的潜在手段(工具).本研究采用高分辨魔角旋转核磁共振氢谱技术结合多维变量分析(如主成分分析)方法研究了30例神经上皮肿瘤组织的代谢特征,并与临床病理结果进行对照.这30例神经上皮肿瘤主要包括2例低级星形细胞瘤(Ⅰ级)、12例中级星形细胞瘤(Ⅱ级)、8例间变型星形细胞瘤(Ⅲ级)、3例胶质母细胞瘤(Ⅳ级)和5例髓母细胞瘤(Ⅳ级).研究发现,神经元(NAA)、肌酸、顺式肌醇、甘氨酸和乳酸等代谢物的浓度以及一些代谢物与肌酸的浓度比值在不同级别的脑肿瘤组织间均具有显著性差别(P<0.05).这些代谢物的浓度比值主要包括NAA/肌酸、乳酸/肌酸、顺式肌醇/肌酸、甘氨酸/肌酸、反式肌醇/肌酸和丙氨酸/肌酸等.此外,采用人为监管模式识别方法建模(SIMCA)来预测(或区分)低、高级肿瘤,准确率基本均达87%.如仅对预测高级(Ⅲ和Ⅳ级)肿瘤而言,其灵敏性和特异性分别高达87%和93%.因此,高分辨魔角旋转核磁共振氢谱技术结合模式识别方法有可能成为未来一种潜在的、快速、准确分级人类脑肿瘤的手段(工具).

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