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NCT Number: NCT06518655

Differentiation of Benign and Malignant Pulmonary Nodules by Volatile Organic Compounds in Human Exhaled Breath

The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) markers. This model aims to accurately differentiate benign from malignant nodules in individuals harboring pulmonary nodules. 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 distinguishing benign and malignant pulmonary nodules. 2. To evaluate the diagnostic effectiveness of an AI model that employs exhaled breath VOC biomakers to identify specific types of malignant nodules, including lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer. 3. To explore and identify key characteristic VOCs combinations that are associated with EGFR site mutations in malignant nodules, further modeling and evaluating the classification performance.

By utilizing this comprehensive approach, the study hopes to contribute significantly to early detection and accurate classification of pulmonary nodules, ultimately leading to improved patient care and treatment outcomes.

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Key information

Conditions

Pulmonary Nodules, Multiple Lung Cancer Lung Diseases Lung Neoplasms Multiple Pulmonary Nodules Neoplasms Neoplasms by Site Pulmonary Nodules, Solitary Respiratory Tract Diseases Respiratory Tract Neoplasms Solitary Pulmonary Nodule Thoracic Neoplasms

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Peking Union Medical College Hospital, Beijing, Beijing Municipality, China

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About this study

This is a prospective, cross-sectional, and observational cohort study aiming at recruiting 3000 participants with pulmonary nodules ranging from 5 to 30 mm in diameter. Prior to invasive surgery, exhaled breath samples will be collected from these participants and analyzed using Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system. Following the acquisition of μGC-PID results, a comprehensive evaluation of the diagnostic performance of VOC biomakers distinguishing between benign and malignant pulmonary nodules will be conducted, leveraging histopathological findings, CT examination data, and clinical data.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 18-80 years old;
  • Pulmonary nodules were detected through low-dose spiral CT, chest CT conventional scan, or high-resolution thin-layer CT examination, with a maximum diameter of 5-30 mm, including solid nodules and ground glass nodules;
  • Patients require pulmonary nodule resection to define the type of nodule pathology;
  • The Patients have not yet used any drugs for tumor treatment;
  • Patients and/or family members are able to understand the research protocol and are willing to participate in this study, providing written informed consent.

Exclusion criteria

  • The maximum diameter of pulmonary nodules is greater than 30 mm;
  • Patients are unable to determine the pathological diagnosis of pulmonary nodules after surgical resection or biopsy;
  • Patients with recurrent lung cancer;
  • Patients who have undergone lung transplantation or lobectomy;
  • Individuals who currently or have a history of malignant tumors;
  • Patients in the acute phase of inflammation or in need of intensive care in the above selected disease groups;
  • Individuals with severe liver and kidney dysfunction;
  • Mental illness patients (such as severe dementia, schizophrenia, severe depression, manic depressive psychosis, etc.);
  • Confirmed HIV patients;
  • Pregnant or lactating women;
  • Patients or family members are unable to understand the conditions and objectives of this study.
  • The patient is unwilling or unable to personally sign the informed consent form.

Treatment and study plan

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

Other

Detection of volatile organic compound molecules in human exhaled breath by GC-MS and μGC-PID

Primary outcomes

  1. The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in distinguishing benign and malignant pulmonary nodules.

    Time frame: 3 years

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

Secondary outcomes

  1. The diagnostic effectiveness of an AI model to identify specific types of malignant nodules, including lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer.

    Time frame: 3 years

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

Other outcomes

  1. Establish an exhaled breath VOC model for predicting EGFR mutations in malignant pulmonary nodules.

    Time frame: 3 years

    Establish an exhaled breath VOC model for predicting EGFR mutations in pathologically confirmed malignant pulmonary nodules. And evaluate the prediction accuracy by comparing the results of EGFR gene testing.

Study contacts

Contact information is provided by the study sponsor or research team.

Hengrui Liang, MD

CONTACT

[email protected]

+86 15625064712

Sponsors and collaborators

Lead sponsor

ChromX Health

Industry

Collaborators

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

Registry information

Official study title

Exploratory Study on the Identification of Benign and Malignant Pulmonary Nodules Using Volatile Organic Compounds in Human Exhaled Breath

Important dates

Study start
2024
Primary completion
2026
Study completion
2027
First posted
Jul 24, 2024
Registry last updated
Dec 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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