2023-04-06 米国国立標準技術研究所(NIST)
本技術は、COPD、肺がん、腎不全など他の疾患も検出可能であり、他の呼気分析技術よりも多くの健康状態を非侵襲的に診断できる可能性を持っています。機械学習アルゴリズムは、それぞれが異なる色や周波数を表す14,836本の櫛の「歯」で測定した呼気サンプルを処理・分析し、病気を診断するための予測モデルを作成します。
<関連情報>
- https://www.nist.gov/news-events/news/2023/04/jilas-frequency-comb-breathalyzer-detects-covid-19-excellent-accuracy
- https://iopscience.iop.org/article/10.1088/1752-7163/acc6e4
超高感度広帯域レーザー分光法による呼気分析でSARS-CoV-2感染症を発見 Breath analysis by ultra-sensitive broadband laser spectroscopy detects SARS-CoV-2 infection
Qizhong Liang, Ya-Chu Chan, Jutta Toscano, Kristen K Bjorkman, Leslie A Leinwand, Roy Parker, Eva S Nozik, David J Nesbitt and Jun Ye
Journal of Breath Research Published: 5 April 2023
DOI:10.1088/1752-7163/acc6e4
Abstract
Rapid testing is essential to fighting pandemics such as coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exhaled human breath contains multiple volatile molecules providing powerful potential for non-invasive diagnosis of diverse medical conditions. We investigated breath detection of SARS-CoV-2 infection using cavity-enhanced direct frequency comb spectroscopy (CE-DFCS), a state-of-the-art laser spectroscopic technique capable of a real-time massive collection of broadband molecular absorption features at ro-vibrational quantum state resolution and at parts-per-trillion volume detection sensitivity. Using a total of 170 individual breath samples (83 positive and 87 negative with SARS-CoV-2 based on reverse transcription polymerase chain reaction tests), we report excellent discrimination capability for SARS-CoV-2 infection with an area under the receiver-operating-characteristics curve of 0.849(4). Our results support the development of CE-DFCS as an alternative, rapid, non-invasive test for COVID-19 and highlight its remarkable potential for optical diagnoses of diverse biological conditions and disease states.
