Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 28;14(1):31542.
doi: 10.1038/s41598-024-83360-0.

Application of Fourier transform infrared spectroscopy to exhaled breath analysis for detecting helicobacter pylori infection

Meiqi Qiu #  1 , Fei Liao #  1 , Yulin Tan  1 , Junlong Zhang  2 , Changjun Zheng  3 , Hanyu Wang  1 , Huangming Zhuang  4 , Wanli Xiong  5 , Qingfang Xie  6 , Weiguo Dong  7
Affiliations

Application of Fourier transform infrared spectroscopy to exhaled breath analysis for detecting helicobacter pylori infection

Meiqi Qiu et al. Sci Rep. .

Abstract

Helicobacter pylori (H. pylori) is one of the most globally prevalent bacteria, closely associated with gastrointestinal diseases such as gastric ulcers and chronic gastritis. Current clinical methods primarily involve Carbon-13 and Carbon-14 urea breath test, both carrying potential safety risks. Fourier-transform infrared (FTIR) spectroscopy can detect human exhaled gases, which may change under disease conditions. This preliminary study aims to explore the application value of FTIR-based breath analysis in detecting H. pylori infection, providing theoretical basis and clinical references for new clinical detection methods. A cross-sectional survey was conducted from August 2021 to May 2022 at Renmin Hospital of Wuhan University. Breath samples were collected before and half an hour after ingesting unlabeled urea. Gas samples were analyzed using FTIR breath spectra. Individual exhalation spectral data after deducting baseline spectral data were used as the basis for the training and test sets through K-center clustering algorithm. Results: A total of 278 samples were collected (63 H. pylori infection cases, 215 healthy controls). There were no statistically significant differences in general data (age, gender, smoking history, alcohol consumption history, comorbidities, etc.) between the two groups. The predictive model was successfully established, with recognition rates of 94.12%, 98.39%, and 91.30% for the training set, test set, and validation set, respectively. Exhaled gas analysis based on Fourier-transform infrared spectroscopy has the potential to diagnose H. pylori infection.

Keywords: Disease diagnosis4; Exhaled gases1; Fourier-transform infrared spectroscopy2; Helicobacter pylori infection3; Optical analysis5.

PubMed Disclaimer

Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Infrared difference preprocessed spectra comparison chart for positive and negative samples.
Fig. 2
Fig. 2
Final predictive model breath test differential diagnosis results chart.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Umar, Z., et al. Rapid diagnosis and precision treatment of Helicobacter pylori infection in clinical settings.Crit. Rev. Microbiol., 2024: p. 1–30. - PubMed
    1. Liou, J. M. et al. 40 years after the discovery of Helicobacter pylori: Towards elimination of H pylori for gastric cancer prevention. Lancet403(10444), 2570–2572 (2024). - PubMed
    1. Hooi, J. K. Y. et al. Global prevalence of helicobacter pylori infection: Systematic review and meta-analysis. Gastroenterology153(2), 420–429 (2017). - PubMed
    1. Zhou, X. Z. et al. Large-scale, national, family-based epidemiological study on Helicobacter pylori infection in China: The time to change practice for related disease prevention. Gut72(5), 855–869 (2023). - PMC - PubMed
    1. Burucoa, C. & Axon, A. Epidemiology of Helicobacter pylori infection. Helicobacter22(Suppl), 1 (2017). - PubMed

LinkOut - more resources