采用便携式拉曼光谱仪对正常、良性和恶性的乳腺癌组织进行检测,通过对其拉曼光谱的指认,归纳了其主要区别和特征.在3类乳腺组织中有明显的脂类的特征峰(1230,1268,1301,1440和1743cm2),而在良性和恶性的组织中,则出现了较为明显的蛋白(1246,1271,1315和1364cm2)和核酸(1340cm2)的特征峰.良性和恶性组织的区别在于恶性组织特有的特征峰(1340cm2),而良性组织所特有的特征峰则应归属为蛋白.在数据分析过程中,选择能够反映样本化学本质的特征峰,利用高斯过程的机器学习对特征峰值建立模型.特异性(0.94)、灵敏度(0.95)和Matthews相关系数(0.86)表明在模型中3种组织有比较良好的辨别度,对于应用拉曼光谱方法辨别正常和患病乳腺组织具有参考价值.
A portable Raman spectrometer was used for distinguishing the characteristics of normal, malignant and benign fresh breast biopsy samples. Based on spectral profiles, the presence of lipids( 1230, 1268, 1301, 1440, 1743 cm-1) is indicated in normal tissue. And proteins(amide I, and amide II1, 1246, 1271, 1315, 1364 cm-1) are found in benign and malignant tissues. Between benign and malignant, nucleic acids( 1340 cm-l ) are found to be good discrimination parameters. In the process of data analysis, the model was set up by Gaussian Process with the intensity of the feature, and obtained the specificity (0. 94), sensibility (0. 95 ) and Matthews correlation coefficient ( MCC, 0. 86 ). This study shows the significance in diagnosing breast disease, and contributes fundamentally to further application on clinic.