The
prototype device non-invasively detects COVID-19 in the exhaled breath of
infected patients, similar to a breathalyzer test for alcohol intoxication.
Few people
who have undergone nasopharyngeal swabs for coronavirus testing would describe
it as a pleasant experience. The procedure involves sticking a long swab up the
nose to collect a sample from the back of the nose and throat, which is then
analyzed for SARS-CoV-2 RNA by the reverse-transcription polymerase chain
reaction (RT-PCR). Now, researchers reporting in ACS Nano have developed a
prototype device that non-invasively detected COVID-19 in the exhaled breath of
infected patients.
In
addition to being uncomfortable, the current gold standard for COVID-19 testing
requires RT-PCR, a time-consuming laboratory procedure. Because of backlogs,
obtaining a result can take several days. To reduce transmission and mortality
rates, healthcare systems need quick, inexpensive and easy-to-use tests. Hossam
Haick, Hu Liu, Yueyin Pan and colleagues wanted to develop a nanomaterial-based
sensor that could detect COVID-19 in exhaled breath, similar to a breathalyzer
test for alcohol intoxication. Previous studies have shown that viruses and the
cells they infect emit volatile organic compounds (VOCs) that can be exhaled in
the breath.
The
researchers made an array of gold nanoparticles linked to molecules that are
sensitive to various VOCs. When VOCs interact with the molecules on a
nanoparticle, the electrical resistance changes. The researchers trained the
sensor to detect COVID-19 by using machine learning to compare the pattern of
electrical resistance signals obtained from the breath of 49 confirmed COVID-19
patients with those from 58 healthy controls and 33 non-COVID lung infection
patients in Wuhan, China. Each study participant blew into the device for 2-3
seconds from a distance of 1¬-2 cm. Once machine learning identified a
potential COVID-19 signature, the team tested the accuracy of the device on a
subset of participants. In the test set, the device showed 76% accuracy in
distinguishing COVID-19 cases from controls and 95% accuracy in discriminating
COVID-19 cases from lung infections. The sensor could also distinguish, with
88% accuracy, between sick and recovered COVID-19 patients. Although the test
needs to be validated in more patients, it could be useful for screening large
populations to determine which individuals need further testing, the
researchers say.