Abstract
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a prevalent
chronic liver disease worldwide. Currently, its diagnosis relies
primarily on imaging and histological examinations, which are
invasive and prone to misdiagnosis in the early stage. To address
these limitations, detection and analysis of volatile organic
compounds (VOCs) in human breath can be a rapid and non-invasive
screening method for NAFLD. In this study, a compact breath
breathalyzer was developed, utilizing a miniaturized gas
chromatography chip with the STM32 microcontroller as the main
control chip to manage airflow, temperature, and receive terminal
signals from the photoionization detector. In the experiment, a gas
mixture comprising five VOCs (pentane, acetone, toluene, octane, and
decane) was selected as the simulated typical disease biomarkers in
human breath to investigate the breathalyzer's performance and
optimize testing conditions for multi-polar and wide-boiling-range
breath samples. Results show that the breathalyzer can detect
low-boiling components (< 100°C) such as the isoprene and
acetone, with a detection limit less than 50 ppb which are two
commonly biomarkers of NAFLD. Furthermore, breath samples were
collected from 35 non-diseased individuals, and NAFLD early-stage
patient samples were simulated by increasing the isoprene
concentration by 10 ppb. Convolutional neural network (CNN) were
used to identify the VOC signatures in gas chromatograms with
predictive accuracy of 85% for the classification model. Therefore,
the compact breath breathalyzer has potential application in the
rapid and early screening of NAFLD.