COVID-19 Detection from Mass Spectra of Exhaled Breath
Nicolò Bellarmino Giorgio Bozzini Riccardo Cantoro Francesco Castelletti Michele Castelluzzo Carla Ciricugno Raffaele Correale Daniela Dalla Gasperina Francesco Dentali Giovanni Poggialini Piergiorgio Salerno Giovanni Squillero Stefano Taborelli
According to the World Health Organization, the SARS-CoV-2 virus generated a
global emergency between 2020 and 2023 resulting in about 7 million deaths out
of more than 750 million individuals diagnosed with COVID-19. During these
years, polymerase-chain-reaction and antigen testing played a prominent role in
disease control. In this study, we propose a fast and non-invasive detection
system exploiting a proprietary mass spectrometer to measure ions in exhaled
breath. We demonstrated that infected individuals, even if asymptomatic,
exhibit characteristics in the air expelled from the lungs that can be detected
by a nanotech-based technology and then recognized by soft-computing
algorithms. A clinical trial was ran on about 300 patients: the mass spectra in
the 10-351 mass-to-charge range were measured, suitably pre-processed, and
analyzed by different classification models; eventually, the system shown an
accuracy of 95% and a recall of 94% in identifying cases of COVID-19. With
performances comparable to traditional methodologies, the proposed system could
play a significant role in both routine examination for common diseases and
emergency response for new epidemics.