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

NCT ID: NCT06528418

Last Updated: 2025-03-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

10000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-06-30

Study Completion Date

2027-06-30

Brief Summary

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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.

Detailed Description

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This is a prospective, cross-sectional, observational cohort study aimed at recruiting 10,000 participants with multiple pulmonary disease, 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 . Exhaled breath samples from these participants will be collected and analyzed using Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system. Upon obtaining the μGC-PID results, a comprehensive evaluation of the diagnostic capabilities of exhaled breath samples in differentiating various pulmonary diseases will be performed, leveraging clinical diagnostic results, CT examination data, and clinical data.

Conditions

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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

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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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 .

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

Intervention Type 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

Individuals with no abnormalities detected in lung CT imaging.

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

Intervention Type 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

Interventions

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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

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* 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.

Exclusion Criteria

* 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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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The First Affiliated Hospital of Guangzhou Medical University

OTHER

Sponsor Role collaborator

First People's Hospital of Foshan

OTHER

Sponsor Role collaborator

Sichuan Cancer Hospital and Research Institute

OTHER

Sponsor Role collaborator

Liwan District Central Hospital

UNKNOWN

Sponsor Role collaborator

Shanghai Chest Hospital

OTHER

Sponsor Role collaborator

Peking Union Medical College Hospital

OTHER

Sponsor Role collaborator

Guangzhou Development Zone Hospital

UNKNOWN

Sponsor Role collaborator

Huangpu District Hongshan Street Community Health Service Center

UNKNOWN

Sponsor Role collaborator

Huangpu District Chinese Medicine Hospital

UNKNOWN

Sponsor Role collaborator

Fifth Affiliated Hospital of Guangzhou Medical University

OTHER

Sponsor Role collaborator

Huangpu District Jiufo Street Community Health Service Center

UNKNOWN

Sponsor Role collaborator

Huangpu District Xinlong Town Central Hospital

UNKNOWN

Sponsor Role collaborator

Huangpu District Yonghe Street Community Health Service Center

UNKNOWN

Sponsor Role collaborator

Huangpu District Lianhe Street Second Community Health Service Center

UNKNOWN

Sponsor Role collaborator

ChromX Health

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jianxing He, MD

Role: STUDY_CHAIR

The First Affiliated Hospital of Guangzhou Medical University

Locations

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The First Affiliated Hospital of Guangzhou Medical University

Guangzhou, Guangdong, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Hengrui Liang, MD

Role: CONTACT

+86 15625064712

Facility Contacts

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Hengrui Liang, MD

Role: primary

+86 15625064712

References

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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.

Reference Type BACKGROUND
PMID: 32526187 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 33374433 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23259710 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 36690293 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 34415806 (View on PubMed)

Other Identifiers

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MLD001

Identifier Type: -

Identifier Source: org_study_id

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