Detection of Exhaled Methane in Gastrointestinal Disease Population Based on TDLAS

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Abstract
Respiratory detection plays a significant role in the assessment of human health status and in aiding the diagnosis of diseases. This requires the development of fast, economical and non-invasive detection technologies. This research employed tunable diode laser absorption spectroscopy (TDLAS) to analyze exhaled methane (CH 4 ) levels in patients with gastrointestinal diseases. The system achieving a minimum detection limit (MDL) of 42.12 ppbv, and an accuracy of 8.04 ppbv. A total of 451 samples of exhaled CH 4 concentration from gastrointestinal surgery patients were detected, and several gastrointestinal diseases with high average CH 4 concentration were screened out. Support vector machine (SVM) algorithms were used to investigate the relationship between CH 4 levels and specific gastrointestinal diseases. The study achieved a classification accuracy, recall, and precision rate of 100% for ileus, ascending colon cancer (COAD), and cancers with liver metastasis. Meantime, the rate of CH 4 positivity for patients undergone postoperative chemotherapy was observed to be significantly lower than patients with active cancer. However, the presence of CH 4 was not significantly associated with gastrointestinal stromal tumors of the stomach (GIST), stomach cancer (SC), or rectal cancer (READ), indicating the need for a multifaceted diagnostic approach incorporating additional gas markers. In conclusion, CH 4 analysis holds promise as a novel non-invasive diagnostic tool for gastrointestinal diseases, with significant potential for clinical application.
Funding Information
  • Key Projects of Education Department of Hebei Province, China (ZD2022072)
  • Science and Technology Plan Project of Hebei Province, China (22321701-D)
  • Hebei Provincial Department of Human Resources and Social Security’s “3-3 Talent Project Funding Project” in Hebei Province (A202101058)
  • Multidisciplinary Interdisciplinary Research Fund of Hebei University (DXK202312)
  • Baoding Science and Technology Plan Project (2372P010, 2394G001, 2494G001)

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