Advanced Center for Treatment Research and Education in Cancer, Chilakapati Laboratory, Kharghar, Navi Mumbai 410210, India.
J Biomed Opt. 2013 Apr;18(4):047004. doi: 10.1117/1.JBO.18.4.047004.
Raman spectroscopy (RS) has been extensively explored as an alternative diagnostic tool for breast cancer. This can be attributed to its sensitivity to malignancy-associated biochemical changes. However, biochemical changes due to nonmalignant conditions like benign lesions, inflammatory diseases, aging, menstrual cycle, pregnancy, and lactation may act as confounding factors in diagnosis of breast cancer. Therefore, in this study, the efficacy of RS to classify pregnancy and lactation-associated changes as well as its effect on breast tumor diagnosis was evaluated. Since such studies are difficult in human subjects, a mouse model was used. Spectra were recorded transcutaneously from the breast region of six Swiss bare mice postmating, during pregnancy, and during lactation. Data were analyzed using multivariate statistical tool Principal Component-Linear Discriminant Analysis. Results suggest that RS can differentiate breasts of pregnant/lactating mice from those of normal mice, the classification efficiencies being 100%, 60%, and 88% for normal, pregnant, and lactating mice, respectively. Frank breast tumors could be classified with 97.5% efficiency, suggesting that these physiological changes do not affect the ability of RS to detect breast tumors.
拉曼光谱（RS）已被广泛探索作为乳腺癌的替代诊断工具。这归因于它对与恶性相关的生化变化的敏感性。然而，由于良性病变、炎症性疾病、衰老、月经周期、怀孕和哺乳等非恶性情况引起的生化变化可能成为乳腺癌诊断的混杂因素。因此，在这项研究中，评估了 RS 对分类与怀孕和哺乳相关的变化的效果及其对乳房肿瘤诊断的影响。由于在人体中进行此类研究具有挑战性，因此使用了小鼠模型。在交配后、怀孕和哺乳期间，从六只瑞士裸鼠的乳房区域经皮记录光谱。使用多元统计工具主成分-线性判别分析对数据进行分析。结果表明，RS 可以区分怀孕/哺乳小鼠的乳房与正常小鼠的乳房，对正常、怀孕和哺乳小鼠的分类效率分别为 100%、60%和 88%。弗兰克乳房肿瘤可以以 97.5%的效率进行分类，表明这些生理变化不会影响 RS 检测乳房肿瘤的能力。
