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作 者:陈瑶[1] 代剑华[1] 张华[2] 周学谦[1] 刘云杰[1] 彭贵勇[1]
机构地区:[1]第三军医大学西南医院全军消化病研究所,重庆400038 [2]中国科学院重庆绿色智能技术研究院跨尺度制造技术重点实验室,重庆400714
出 处:《激光生物学报》2014年第1期45-50,共6页Acta Laser Biology Sinica
基 金:国家自然科学基金项目(81272580)
摘 要:目的:分析研究胃正常和癌变粘膜组织的拉曼光谱特征,为拉曼光谱应用于胃癌的临床检测诊断奠定基础。方法:收集胃镜检查中活检的19例正常和12例癌变胃粘膜组织标本,采用785 nm激发光拉曼光谱仪进行拉曼光谱采集。比较分析胃正常和癌变粘膜组织的拉曼光谱特征差异并研究其区分正常和癌变组织的价值。结果:1)特征峰1 098 cm-1、1 444 cm-1、1 555 cm-1、1 660 cm-1等在胃癌组织中发生了移位,平均位移(2.57±1.28)cm-1,以红移为主;2)癌变组织中相对峰强比I1087 cm-1/I1207 cm-1≥1.87,其区别胃癌和正常胃粘膜组织的准确率、灵敏度和特异度分别为87.1%、83.3%、89.5%;3)癌组织中增加了表征蛋白质的特征峰1 262 cm-1、1 586 cm-1,但同时减少了表征蛋白质和脂质特征峰1 172 cm-1。结论:拉曼光谱不仅可以准确区分正常和癌变,而且可以探索癌变相关的分子生化改变。拉曼光谱在胃癌的跟踪发现和检测诊断中具有良好前景。Object:Raman spectra features of normal and malignant gastric mucosal tissues were analysed to pave the way for Raman Spectroscopy being applied to clinical tumor detection and diagnosis.Methods:A total of 3 1 gastric tis-sues were collected for Raman Spectroscopic measurements with a rapid-acquisition NIR-Raman system at 785-nm exci-tion.With a comparitive study of Raman spectrums aquired respectively from normal and malignant gastric mucosal tis-sues,its potential in discriminating normal from malignant gastric tissues can be further evaluated.Results:1 )Some characteristic peaks shifted in malignant tissues,e.g.peaks at 1 098 cm-1、1 444 cm-1、1 555 cm-1、1 660 cm-1 and so on,which were mainly red shift,and the average shift was about 2.57 ±1.28 cm-1;2)The ratio of relative intensity,I1 087 cm-1/I1 207 cm-1,is not less than 1.87 in gastric tissues,which yielded a diagnosis accuracy of 87.1%,sensitivity of 83 .3% and specificity of 89 .5% respectively;3 )An extra characteristic peak indicating protein appeared at 1 262 cm-1 in cancer tissues,while another characteristic peak indicating lipid and protein at 1 172 cm-1 disappeared.Conclusion:Raman spectroscopy can not only discriminate cancer from normal tissues accurately,but also has great potential in pro-bing biomolecular alteration associated with canceration.Raman spectroscopy has show excellent application prospects in gastric cancer detection and diagnosis.
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