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

NCT06528418 | Recruiting

• 1 other identifier: MLD001
• Study Type: observational
• Target: 10,000
• Locations: 1 country
• Sites: 1

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

Keywords

Pulmonary Disease; Volatile Organic Compounds; Human Exhaled Breath; micro Gas Chromatography-photoionisation; detector (μGC-PID) system

Outcome Measures

Primary Outcomes (1)

• The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in the diagnosis of several common pulmonary diseases.

  The diagnostic performance of the exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model will be compared with clinical diagnosis and CT/LDCT diagnosis, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

  2 years

Secondary Outcomes (1)

• The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in the diagnosis of more pulmonary diseases.

  2 years

Other Outcomes (1)

• Establish an exhaled breath VOC model for predicting specific gene mutations in some lung diseases.

  2 years

Study Arms (2)

pulmonary disease

Individuals with abnormalities in lung CT imaging and clinically diagnosed with lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm) etc .

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

normal individual

Individuals with no abnormalities detected in lung CT imaging.

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

Interventions

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

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

normal individual; pulmonary disease

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with abnormal lung CT images within the past six months, including lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm), etc .

You may qualify if:

• Males or females, age must be 18 years old or above.
• Patients must meet the CT imaging diagnostic criteria for different lung diseases, and patients must be able to provide electronic versions of CT image data.
• Patients must have a clear clinical diagnosis.
• All participants must sign a written informed consent form.

You may not qualify if:

• Pregnant women.
• Individuals with a history of cancer other than lung disease.
• Individuals who have undergone organ transplants or non-autologous (allogeneic) bone marrow or stem cell transplants.
• Individuals with other severe organic diseases or mental illnesses.
• Individuals with metabolic diseases such as diabetes, hyperlipidemia, etc.
• Any other condition that researchers deem unsuitable for participation in this clinical trial.

Sponsors & Collaborators

• ChromX Health: lead
• The First Affiliated Hospital of Guangzhou Medical University: collaborator
• First People's Hospital of Foshan: collaborator
• Sichuan Cancer Hospital and Research Institute: collaborator
• Liwan District Central Hospital: collaborator
• Shanghai Chest Hospital: collaborator
• Peking Union Medical College Hospital: collaborator
• Guangzhou Development Zone Hospital: collaborator
• Huangpu District Hongshan Street Community Health Service Center: collaborator
• Huangpu District Chinese Medicine Hospital: collaborator
• Fifth Affiliated Hospital of Guangzhou Medical University: collaborator
• Huangpu District Jiufo Street Community Health Service Center: collaborator
• Huangpu District Xinlong Town Central Hospital: collaborator
• Huangpu District Yonghe Street Community Health Service Center: collaborator
• Huangpu District Lianhe Street Second Community Health Service Center: collaborator

Study Sites (1)

The First Affiliated Hospital of Guangzhou Medical University

Guangzhou, Guangdong, 510140, China

RECRUITING

Related Publications (5)

• GBD Chronic Respiratory Disease Collaborators. Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med. 2020 Jun;8(6):585-596. doi: 10.1016/S2213-2600(20)30105-3.

  PMID: 32526187 BACKGROUND

• Ratiu IA, Ligor T, Bocos-Bintintan V, Mayhew CA, Buszewski B. Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD. J Clin Med. 2020 Dec 24;10(1):32. doi: 10.3390/jcm10010032.

  PMID: 33374433 BACKGROUND

• van de Kant KD, van der Sande LJ, Jobsis Q, van Schayck OC, Dompeling E. Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review. Respir Res. 2012 Dec 21;13(1):117. doi: 10.1186/1465-9921-13-117.

  PMID: 23259710 BACKGROUND

• Wang J, Janson C, Gislason T, Gunnbjornsdottir M, Jogi R, Orru H, Norback D. Volatile organic compounds (VOC) in homes associated with asthma and lung function among adults in Northern Europe. Environ Pollut. 2023 Mar 15;321:121103. doi: 10.1016/j.envpol.2023.121103. Epub 2023 Jan 21.

  PMID: 36690293 BACKGROUND

• V A B, Subramoniam M, Mathew L. Noninvasive detection of COPD and Lung Cancer through breath analysis using MOS Sensor array based e-nose. Expert Rev Mol Diagn. 2021 Nov;21(11):1223-1233. doi: 10.1080/14737159.2021.1971079. Epub 2021 Aug 27.

  PMID: 34415806 BACKGROUND

Biospecimen

Retention: SAMPLES WITHOUT DNA

Volatile Organic Compounds in Human Exhaled Breath

MeSH Terms

Conditions

Lung Neoplasms; Pulmonary Disease, Chronic Obstructive; Bronchitis; Pulmonary Fibrosis; Pulmonary Embolism; Pulmonary Arterial Hypertension; Tuberculosis, Pulmonary; Lung Abscess; Emphysema; Lung Injury; Cystic Fibrosis; Asthma; Bronchiectasis; Lung Diseases, Interstitial; Lung Diseases

Interventions

Drug Delivery Systems

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Respiratory Tract Diseases; Lung Diseases, Obstructive; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Respiratory Tract Infections; Infections; Bronchial Diseases; Fibrosis; Embolism; Embolism and Thrombosis; Vascular Diseases; Cardiovascular Diseases; Hypertension, Pulmonary; Tuberculosis; Mycobacterium Infections; Actinomycetales Infections; Gram-Positive Bacterial Infections; Bacterial Infections; Bacterial Infections and Mycoses; Abscess; Suppuration; Thoracic Injuries; Wounds and Injuries; Pancreatic Diseases; Digestive System Diseases; Genetic Diseases, Inborn; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Infant, Newborn, Diseases; Respiratory Hypersensitivity; Hypersensitivity, Immediate; Hypersensitivity; Immune System Diseases

Intervention Hierarchy (Ancestors)

Drug Therapy; Therapeutics

Study Officials

• Jianxing He, MD

  The First Affiliated Hospital of Guangzhou Medical University

  STUDY CHAIR

Central Study Contacts

Hengrui Liang, MD

CONTACT

+86 15625064712; hengrui_liang@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 18, 2024
• First Posted: July 30, 2024
• Study Start: June 30, 2024
• Primary Completion (Estimated): December 30, 2026
• Study Completion (Estimated): June 30, 2027
• Last Updated: March 26, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)