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通过质谱法进行呼吸分析:乳腺癌检测的新工具?

Breath analysis by mass spectrometry: a new tool for breast cancer detection?

作者信息

Patterson Sharla Gayle, Bayer Charlene W, Hendry Robert J, Sellers Nancy, Lee Kichun Sky, Vidakovic Brani, Mizaikoff Boris, Gabram-Mendola Sheryl G A

机构信息

Emory Winship Cancer Institute, Atlanta, Georgia, USA.

出版信息

Am Surg. 2011 Jun;77(6):747-51.

PMID:21679645
Abstract

Breath analysis has received attention as a noninvasive diagnostic tool with increasing research into its potential usefulness. We are investigating the utility of the analysis of breath volatile organic compounds (VOCs) as an effective modality for breast cancer (BC) detection and monitoring by collecting breath samples with a simple portable device to determine whether BC patients have breath VOCs distinct from those in healthy volunteers. We prospectively enrolled 20 healthy volunteers and 20 newly diagnosed stage II-IV BC patients. The study subjects deeply exhaled into a commercially available Teflon/valved breath sampler equipped with a rapid passive diffusive sampler five times at 5-minute intervals trapping alveolar breath VOCs. The exhaled breath samples were analyzed by thermal desorption/gas chromatography/mass spectrometry monitoring 383 VOCs in the breath of both populations. Our results indicate that aggregate low-dimensional summaries and compound quantities result in specific patterns that can confirm BC. We found a definite clustering of the presence of BC from cancer-free points. Overall sensitivity was 72 per cent and specificity was 64 per cent resulting in a correct classification rate of approximately 77 per cent. Our data show promising evidence that BC patients can be differentiated from healthy volunteers through distinct breath VOCs.

摘要

随着对呼气分析潜在用途的研究不断增加,呼气分析作为一种非侵入性诊断工具受到了关注。我们正在研究通过使用一种简单的便携式设备收集呼气样本,分析呼气挥发性有机化合物(VOCs)作为检测和监测乳腺癌(BC)的有效方式的效用,以确定BC患者的呼气VOCs是否与健康志愿者不同。我们前瞻性地招募了20名健康志愿者和20名新诊断的II-IV期BC患者。研究对象每隔5分钟向配备快速被动扩散采样器的市售聚四氟乙烯/带阀呼气采样器中深呼气5次,以捕获肺泡呼气VOCs。通过热解吸/气相色谱/质谱法分析呼出的呼气样本,监测两组人群呼气中的383种VOCs。我们的结果表明,聚合的低维汇总和化合物数量会产生可确认BC的特定模式。我们发现BC的存在与无癌点有明确的聚类。总体敏感性为72%,特异性为64%,正确分类率约为77%。我们的数据显示了有希望的证据,即BC患者可以通过独特的呼气VOCs与健康志愿者区分开来。

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