关键词: 乳腺肿瘤, 拉曼光谱, 主成分分析, 模型构建

Abstract:

Abstract:Objective To explore the application value of  portable Raman spectroscopy  in fresh breast lesions and normal breast tissues, and to clarify the application value of  principal component analysis (PCA) method in Raman spectrascopy detetion results, construction of  the mathematical model  and differential diagnosis.Methods The fresh tissues of 168 patients (all female,aged 22-75 years) were obtained by routine surgical resection from Department of Breast Surgery,the First Hospital of Jilin University.51 normal tissues,66 benign and 51 malignant breast lesions were detected by Raman spectroscopy.The PCA algorithm was used to process the data and build the mathematical model.Mahalanobis distance and spectral residuals were used as discriminating criteria for evaluating this method.Results 1 800 Raman spectra were acquired from fresh samples of human breast tissues.Based on spectral profiles,the presence of 1 078,1 267,1 301,1 440,1 654,and 1 746 cm-1 were indicated in normal tissues.And 1 281,1 341,1 381,1 417,1 465,1 530,and 1 637 cm-1 were found in benign and malignant tissues.The main differences of benign and malignant were the characteristic peaks of 1 340 and 1 480 cm-1.The accuracies of PCA were 80%,56%,and 85% in discriminating normal,benign and malignant tissues.Conclusion Portable Raman spectra can detect the breast tissues and lesions.The Raman spectra of normal,benign and malignant breast tissues have significant differences.PCA method can be used to build identification model,but there is still insufficient in distinguishing benign lesion tissues.

Key words: breast neoplasms, Raman spectroscopy, principal component analysis, model construction