Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

作者：Morad K. Nakhleh, Haitham Amal, Raneen Jeries, Yoav Y. Broza, Manal Aboud, Alaa Gharra, Hodaya Ivgi, Salam Khatib, Shifaa' Badarneh, Lior Har‐Shai, Lea Glass‐Marmor, Izabella Lejbkowicz, Ariel Miller, Samih Badarny, Raz Winer, J. P. M. Finberg, Sylvia Cohen‐Kaminsky, Frédéric Perros, David Montani, Barbara Girerd, Gilles Garcia, Gérald Simonneau, Farid Nakhoul, Shira Baram, Raed Salim, Marwan Hakim, Maayan Gruber, Ohad Ronen, Tal Marshak, Ilana Doweck, Ofer Nativ, Zaher Bahouth, Dayou Shi, Wei Zhang, Qingling Hua, Yue-yin Pan, Tao Li, Hu Liu, Amir Karban, Eduard Koifman, Tova Rainis, Roberts Škapars, Armands Sīviņš, Guntis Ancāns, Inta Liepniece‐Karele, Ilze Ķikuste, Ieva Lašina, Ivars Tolmanis, Douglas Johnson, Stuart Z. Millstone, Jennifer A. Fulton, John W. Wells, L HABELSON WILF, Marc Humbert, Mārcis Leja, Nir Peled, Hossam Haick · 发表于：ACS Nano · 年份：2016 · DOI：10.1021/acsnano.6b04930 · 被引用次数：504 · 研究领域：Advanced Chemical Sensor Technologies、Gas Sensing Nanomaterials and Sensors、Analytical Chemistry and Chromatography

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from ...