通过表面增强的拉曼光谱法诊断和分类与尿液的肠道疾病
Silong Li1, Yuqing Zheng1, Yiheng Yang2
1School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|February 29, 2024
概括
这项研究引入了一种使用表面增强拉曼光谱 (SERS) 进行早期肠道疾病 (ID) 诊断的新型尿液测试. 该方法可以准确地区分健康人群和ID患者,并区分良性肠道疾病和结直肠癌.
科学领域:
- 生物分子光谱学
- 医学诊断 医学诊断 医学诊断
- 胃肠病学 胃肠病学
背景情况:
- 肠道疾病 (ID) 构成重大健康风险,包括癌症,需要早期和准确的诊断.
- 传统的ID诊断方法往往缺乏足够的敏感性和特异性.
- 使用易于获取的样本,如尿液等的非侵入性诊断方法是非常可取的.
研究的目的:
- 开发一种使用尿液分析进行肠道疾病的敏感,非侵入性诊断方法.
- 建立分类模型,以区分健康对照和ID患者.
- 要区分良性肠道疾病 (BID) 和结直肠癌 (CRC),使用尿液SERS.
主要方法:
- 利用表面增强的拉曼光谱法 (SERS) 来分析830个人的尿样 (100个健康对照,443个BID,287个CRC).
- 开发了主要组件分析 (PCA) - 支持矢量机 (SVM) 分类模型,用于ID/HC和BID/CRC的歧视.
- 经过验证的模型使用离开一次的交叉验证 (LOOCV) 和BID/CRC的外部测试集.
主要成果:
- 通过LOOCV实现了ID/HC分类的86.4%准确度和BID/CRC分类的85.56%准确度.
- 对于BID/CRC模型的外部测试组显示了82.14%的准确性.
- 尿液的SERS分析显示在识别ID和分类疾病亚型方面具有很高的准确性.
结论:
- 拟议的尿液SERS方法为早期检测肠道疾病提供了有价值的工具.
- 开发的分类模型提供了健康个体,BID和CRC之间的可靠歧视.
- 这种非侵入性诊断方法可以帮助临床医生及时进行ID诊断和分期.
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