使用FTIR和拉曼光谱融合技术对异常性复发性自发性流产的分类
Dadoma Sherpa1, Chiranjib Bhowmick1, Tummala Pavan2
1School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India.
Systems biology in reproductive medicine
|August 16, 2024
概括
异常性复发性自发性流产 (IRSM) 缺乏明确的诊断指南. 将子宫内膜组织的拉曼光谱和FTIR光谱结合起来,显著提高了IRSM分类的准确性,提供了一种有前途的新诊断方法.
科学领域:
- 生物医学光谱学 生物医学光谱学
- 生殖医学 生殖医学
- 数据融合数据融合
背景情况:
- 异常性复发性自发性流产 (IRSM) 影响了近50%的复发性流产病例,诊断和管理准则定义不佳.
- 目前对IRSM的诊断方法缺乏可靠的科学证据,需要新的方法来准确识别和分类.
研究的目的:
- 探索振动光谱学的潜力,特别是拉曼和减弱总反射率-里埃变换红外光谱 (ATR-FTIR),用于诊断IRSM.
- 开发和评估光谱数据融合策略,以提高IRSM分类的诊断准确性.
主要方法:
- 在植入窗口期间,从IRSM (n=20) 和对照组 (n=20) 的妇女收集了子宫内膜组织样本.
- 获得了拉曼和ATR-FTIR光谱,随后进行了数据预处理,包括主要组件分析 (PCA) 和波段值排斥 (WTD).
- 使用机器学习模型分析了融合的光谱数据:支持矢量机器 (SVM),自适应增强 (AdaBoost) 和决策树 (DT).
主要成果:
- 拉曼光谱检测显示,IRSM中与蛋白质,谷氨酸和脂质代谢相关的分子振动发生变化.
- 在IRSM患者中,ATR-FTIR分析显示了脂质,蛋白质,原和葡萄糖代谢的变化.
- 频谱数据融合,特别是中级和高级融合,实现了高达92%的IRSM分类精度,优于单个光谱方法.
结论:
- 拉曼和ATR-FTIR数据的光谱融合显示了提高异常性复发性自发性流产的诊断准确性的巨大潜力.
- 这种方法在临床环境中为IRSM诊断提供了一个有希望的非侵入性工具,等待在更大的患者队伍中验证.
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