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在食道癌的诊断中使用血清挥发性有机化合物
Qi Liu1,2, Shuhai Li3, Mai Mao1,2
1Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, 250012, Shandong, China.
Scientific reports
|July 31, 2024
概括
血清挥发性有机化合物 (VOC) 是食道癌 (EC) 的早期诊断生物标志物. 一项使用气相色谱-离子移动谱和机器学习的研究在检测血清VOC中的EC方面取得了很高的准确性.
科学领域:
- 在瘤学瘤学.
- 分析化学 分析化学
- 生物标志物 生物标志物
背景情况:
- 由于缺乏有效的查工具,食道癌 (EC) 的早期诊断仍然是一个重大的临床挑战.
- 血清中的挥发性有机化合物 (VOC) 是新型诊断生物标志物的潜在,非侵入性来源.
研究的目的:
- 研究血清挥发性有机化合物 (VOC) 作为食道癌 (EC) 的潜在诊断生物标志物的实用性.
- 评估机器学习模型在基于血清VOC配置文件的EC分类中的性能.
主要方法:
- 来自55名EC患者和84名健康对照者的血清样本使用气体染色体离子运动谱法 (GC-IMS) 进行了分析,以检测VOC.
- 机器学习算法应用于GC-IMS数据,重点关注33个检测到的物质峰值高度.
- 采用接收器操作特征 (ROC) 分析来评估诊断模型的性能.
主要成果:
- 四种不同的机器学习模型在诊断EC时表现出有效性.
- 随机森林模型利用5种特定的VOC,实现了0.951.95的曲线下的高面积 (AUC).
- 该模型表现出极好的诊断性能,灵敏度为94.1%,特异性为96.0%.
结论:
- 通过GC-IMS检测到的血清VOCs,当用机器学习分析时,可以作为有效的生物标志物用于食道癌症诊断.
- 随机森林模型显示了准确和非侵入性EC检测的巨大潜力,需要进一步的临床验证.
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