Study of Breath Biomarkers to Identify and Diagnose Various Lung Diseases Using Advanced AI Technology

What this Trial Is About

Researchers are studying how to use exhaled breath volatile organic compound VOC markers and artificial intelligence AI to diagnose multiple lung diseases. This observational study aims to develop an advanced AI model that helps identify various common and additional pulmonary diseases, including lung cancer, infections, COPD, bronchitis, fibrosis, and others. Participants will provide breath samples analyzed by Gas chromatography-mass spectrometry GC-MS and micro Gas Chromatography-photoionisation detector GC-PID systems. The study includes people with lung disease diagnosed by CT scans and clinical evaluation, as well as individuals with no lung abnormalities on CT imaging. This cross-sectional study plans to enroll up to 10,000 participants. During the study, breath samples and clinical data including CT results will be collected and analyzed to assess the AI models accuracy in diagnosing lung diseases. The primary outcome is the models diagnostic accuracy over two years. Participants may undergo clinical diagnosis reviews, CT exams, and breath testing. The study runs until mid-2027 and includes healthy volunteers aged 18 to 100 years.

Identification of Multiple Pulmonary Diseases Using Volatile Organic Compounds Biomarkers in Human Exhaled Breath