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

Summary

The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) marker molecules. This model aims to accurately diagnose mutiple pulmonary diseases. The primary objectives it strives to accomplish are:

1. To assess the diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in diagnose several common pulmonary diseases.
2. To assess the diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in diagnose more pulmonary diseases.

Conditions

• Lung Cancer
• Lung Infection
• COPD
• Bronchitis
• Pulmonary Fibrosis
• Pulmonary Embolism
• Pulmonary Arterial Hypertension
• Pulmonary Tuberculosis
• Pulmonary Abscess
• Emphysema
• Lung Injury
• Cystic Fibrosis of the Lung
• Bronchial Asthma
• Bronchiectasis
• Interstitial Lung Disease
• Preserved Ratio Impaired Spirometry

Interventions

OTHER

Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system

Exhaled breath samples from these participants will be collected and analyzed to detect volatile organic compound molecules in human exhaled breath by GC-MS and μGC-PID

Sponsors & Collaborators

• The First Affiliated Hospital of Guangzhou Medical University

  collaborator OTHER

• First People's Hospital of Foshan

  collaborator OTHER

• Sichuan Cancer Hospital and Research Institute

  collaborator OTHER

• Liwan District Central Hospital

  collaborator UNKNOWN

• Shanghai Chest Hospital

  collaborator OTHER

• Peking Union Medical College Hospital

  collaborator OTHER

• Guangzhou Development Zone Hospital

  collaborator UNKNOWN

• Huangpu District Hongshan Street Community Health Service Center

  collaborator UNKNOWN

• Huangpu District Chinese Medicine Hospital

  collaborator UNKNOWN

• Fifth Affiliated Hospital of Guangzhou Medical University

  collaborator OTHER

• Huangpu District Jiufo Street Community Health Service Center

  collaborator UNKNOWN

• Huangpu District Xinlong Town Central Hospital

  collaborator UNKNOWN

• Huangpu District Yonghe Street Community Health Service Center

  collaborator UNKNOWN

• Huangpu District Lianhe Street Second Community Health Service Center

  collaborator UNKNOWN

• ChromX Health

  lead INDUSTRY

Principal Investigators

• Jianxing He, MD · The First Affiliated Hospital of Guangzhou Medical University

Eligibility

Min Age

18 Years

Max Age

100 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2024-06-30

Primary Completion

2026-12-30

Completion

2027-06-30

Countries

• China

Study Locations