The Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, 32000 Haifa, Israel.
Breast Cancer Res Treat. 2011 Apr;126(3):791-6. doi: 10.1007/s10549-010-1317-x. Epub 2010 Dec 29.
Certain benign breast diseases are considered to be precursors of invasive breast cancer. Currently available techniques for diagnosing benign breast conditions lack accuracy. The purpose of this study was to deliver a proof-of-concept for a novel method that is based on breath testing to identify breast cancer precursors. Within this context, the authors explored the possibility of using exhaled alveolar breath to identify and distinguish between benign breast conditions, malignant lesions, and healthy states, using a small-scale, case-controlled, cross-sectional clinical trial. Breath samples were collected from 36 volunteers and were analyzed using a tailor-made nanoscale artificial NOSE (NA-NOSE). The NA-NOSE signals were analyzed using two independent methods: (i) principal component analysis, ANOVA and Student's t-test and (ii) support vector machine analysis to detect statistically significant differences between the sub-populations. The NA-NOSE could distinguish between all studied test populations. Breath testing with a NA-NOSE holds future potential as a cost-effective, fast, and reliable diagnostic test for breast cancer risk factors and precursors, with possible future potential as screening method.
某些良性乳腺疾病被认为是浸润性乳腺癌的前兆。目前用于诊断良性乳腺疾病的技术准确性不足。本研究旨在为一种基于呼吸测试的新型方法提供概念验证,以识别乳腺癌的前兆。在这方面,作者探索了使用呼气肺泡呼吸来识别和区分良性乳腺疾病、恶性病变和健康状态的可能性,使用了小规模、病例对照、横断面临床试验。从 36 名志愿者中收集了呼吸样本,并使用定制的纳米级人工嗅觉(NA-NOSE)进行了分析。使用两种独立的方法分析了 NA-NOSE 信号:(i)主成分分析、方差分析和学生 t 检验,(ii)支持向量机分析,以检测子群体之间的统计学显著差异。NA-NOSE 可以区分所有研究的测试人群。使用 NA-NOSE 进行呼吸测试具有作为乳腺癌危险因素和前兆的具有成本效益、快速和可靠的诊断测试的未来潜力,并且可能具有作为筛查方法的未来潜力。