Industry News | 2025 ELCC Ailiben Technology PTR-TOF MS Facilitates a New Era of exhaled Breath Cancer Detection

Dr. Huang Chen, representative of West China Hospital of Sichuan University

The 2025 European Congress on Lung Cancer (ELCC) was held in Paris, France from March 26th to 29th. As one of the most influential international academic conferences in the field of global lung cancer research, this year's conference brought together over 2,000 experts and scholars from more than 40 countries to jointly showcase the latest research progress and achievements in the diagnosis and treatment of lung cancer. Two research achievements of the team led by Director Huang Yan and Dr. Huang Chen from West China Hospital of Sichuan University have been successfully selected for the Poster presentation session of this conference.

Dr. Huang Yan

Deputy Director of the General Practice Center and Deputy Director of the Health Management Center, West China Hospital of Sichuan University, Doctor, Chief Physician.

Skilled in the health management of respiratory system diseases, with the main clinical direction being the early diagnosis of lung cancer.

What is exhaled breath testing?

Exhaled breath testing is a medical diagnostic method, which diagnoses diseases by testing the components and contents of volatile organic compounds in human exhaled breath. It can provide a brandnew screening and differential diagnosis solution for the early screening of tumors and infectious diseases.

PTR-TOF MS

PTRMS is a soft ionization mass spectrometry technology based on proton transfer reactions, which is a direct reading analysis method through the ionization of gas-phase hydrated hydrogen ions as reagent ions. Due to its high sensitivity and ease of use, it can be widely applied in fields such as medical research, environmental research, and biological research.

In the field of medical diagnosis, Ailiben Technology has been continuously conducting early screening research on various diseases such as lung cancer, gastric cancer, breast cancer, diabetes, and anesthetic metabolism based on human exhaled breath in collaboration with multiple institutions including West China Hospital of Sichuan University. After crossvalidation, the accuracy rate of this technology in the early screening of lung cancer has reached more than 90%. The team has obtained the Class II medical registration certificate and production certificate for the human exhaled gas detection mass spectrometer.

This instrument features high sensitivity and high resolution, with a detection limit reaching the ppt level, and is capable of accurately analyzing trace substances. A single instrument can simultaneously conduct qualitative and quantitative detection of hundreds of gases, breaking through the bottleneck at the level of exhaled gas diagnostic detection equipment. On the premise of ensuring a high accuracy rate (with an accuracy rate exceeding 90% and a detection rate within 10%), low-cost, highly accessible and non-invasive detection has also been achieved.

Study on sereening and diagnosis model of smokers based on PTR-TOF-MS

This study relied on proton transfer reaction time-of-flight mass spectrometry (PTTR-TOF MS) technology to conduct an in-depth analysis of the expiratory metabolomics of 3,942 subjects (among them, 2,998 were non-smokers and 944 were smokers), and based on this, a prediction model was derived to accurately identify smokers. In the construction of the non-smoker and smoker models, the accuracy of the training set was as high as 99.88%, the accuracy of the validation set was 92.34%, the accuracy of the test set was 94.89%, the sensitivity reached 95.59%, the specificity was 94.20%, and the area under the curve (AUC) value was 0.9688. The research results show that there are significant differences in metabolites between smokers and non-smokers.

A multicenter exhaled breath metabolomics lung cancer screening model based on PTR-TOF MS

The research team prospectively recruited subjects at West China Hospital of Sichuan University from October 2022 to April 2023. The data set was evaluated using the confusion matrix and ROC curve. The XGBoost algorithm was used to model and analyze the data of non-lung cancer patients and lung cancer patients, healthy individuals and lung cancer patients, pulmonary nodules and lung cancer patients. It was found that the prediction model based on PTR-TOF MS could effectively distinguish lung cancer patients from non-lung cancer patients (including healthy people and patients with benign pulmonary nodules), and had good accuracy, sensitivity and specificity. Compared with other traditional detection methods, PTR-TOF MS has a faster analysis speed, higher accuracy and a wider detection range of mass spectrometry. Although the analysis of VOCs has not been widely applied in clinical practice at present, the existing research evidence indicates that it has great clinical value. Through in-depth research, the relationship between VOCs and the staging of lung cancer can be more clearly defined, thereby promoting the early screening and diagnosis of lung cancer and enabling treatment to be initiated as soon as possible.

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