基于血清表面增强拉曼光谱和多元统计分析的宫颈癌快速检测
首发时间:2024-03-27
摘要:在女性中,宫颈癌(CC)是一种最常见的恶性肿瘤,了解宫颈癌的分子机制在宫颈癌的诊断和治疗中发挥重要作用。在这项研究中,探索了表面增强拉曼光谱(SERS)与多元统计分析(MSA)相结合诊断宫颈癌的潜力。从95例CC患者,81例健康受试者中收集血清样本,使用MSA分析光谱数据,包括主成分分析结合支持向量机(PCA-SVM)、偏最小二乘判别分析(PLS-DA)和与正交偏最小二乘判别分析(OPLS-DA)。结果显示,PLS-DA的效果最好,预测准确率为97.73%,灵敏度和特异性分别为100%,95.83%。目前的结果表明,血清SERS技术与MSA相结合,有望成为快速筛查宫颈癌的新型临床工具
关键词: 疾病诊断 宫颈癌 表面增强拉曼光谱 多元统计分析 血清
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Rapid detection of cervical cancer based on serum surface enhanced Raman spectroscopy and multivariate statistical analysis
Abstract:Among women, cervical cancer (CC) stands as one of the most prevalent malignancies, and understanding the molecular mechanisms of CC plays a crucial role in its diagnosis and treatment. This study explores the potential of combining surface-enhanced Raman spectroscopy (SERS) with multivariate statistical analysis (MSA) for diagnosing cervical cancer. Serum samples were collected from 95 CC patients and 81 healthy controls. MSA was employed to analyze spectral data, utilizing techniques such as principal component analysis combined with support vector machine (PCA-SVM), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results indicate that PLS-DA performed the best, achieving a predictive accuracy of 97.73%, with sensitivity and specificity of 100% and 95.83%, respectively. These findings suggest that the integration of serum SERS technology with MSA holds promise as a novel clinical tool for rapid screening of cervical cancer.
Keywords: Disease diagnosis Cervical cancer Surface enhanced Raman spectroscopy Multivariate statistical analysis Serum
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基于血清表面增强拉曼光谱和多元统计分析的宫颈癌快速检测
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