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Pulmonary Nodules, MultipleNCT06518655

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

An observational study of Pulmonary Nodules, Multiple and Pulmonary Nodules, Solitary, run by ChromX Health at 15 sites in China.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record
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Trial summary

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. Read more about this study

Who is it for?
Ages 18 to 80 yearsHealthy volunteers can take part
What is being tested?
Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system
How many people
3,000 participants
Where
15 sitesChina
Study dates
30 Jun 2024to 30 Jun 2027
Phase
Observational
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 80 years
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Study population: People who have pulmonary nodules with a large diameter between 5 mm and 30 mm on a CT scan within six months.

Who may be able to join

  • 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.

Who cannot join

  • 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;
Show all 12Show fewer
  • 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.

Trial locations and contacts

15 sites in 1 country. Contact the study team or a site near you to ask about taking part.

Hengrui Liang, MD contact

+86 15625064712

hengrui_liang@163.com

15 sites in 1 country

China15 sites, 15 recruiting

  • Peking Union Medical College Hospital

    Beijing, Beijing Municipality

    Qian Wang, MD

    Recruiting

  • Sichuan Cancer Hospital

    Chengdu, Sichuan, 610042

    Bo Tian, MD, +86 18980053101

    Recruiting

  • First People's Hospital of Foshan

    Foshan, Guangdong, 528000

    Zhuxing Chen

    Recruiting

  • The First Affiliated Hospital of Guangzhou Medical University

    Guangzhou, Guangdong, 510140

    Hengrui Liang, MD, +86 15625064712, hengrui_liang@163.com

    Recruiting

  • Liwan District Central Hospital

    Guangzhou, Guangdong, 510175

    Hengrui Liang, MD

    Recruiting

  • Guangzhou Development Zone Hospital

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Chinese Medicine Hospital

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Hongshan Street Community Health Service Center

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Jiufo Street Community Health Service Center

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Lianhe Street Second Community Health Service Center

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Xinlong Town Central Hospital

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Huangpu District Yonghe Street Community Health Service Center

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • The Fifth Affiliated Hospital of Guangzhou Medical University

    Guangzhou, Guangdong

    Hengrui Liang, MD

    Recruiting

  • Shanghai Chest Hospital

    Shanghai, Shanghai Municipality

    Yanwei Zhang, MD

    Recruiting

  • Renmin Hospital of Wuhan University

    Wuhan, Hubei

    Huiqing Lin, MD

    Recruiting

Other trials in China

About this study

Official title: Exploratory Study on the Identification of Benign and Malignant Pulmonary Nodules Using 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.

Read the detailed description

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.

Being tested
Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system
Keywords
Pulmonary Nodules, Lung Cancer, Volatile Organic Compounds, Human Exhaled Breath
Medical subject headings
Multiple Pulmonary Nodules, Solitary Pulmonary Nodule, Lung Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

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

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

Study groups in NCT06518655
Study groupRoleWhat they receive
Pulmonary NodulesPre-surgery adult patients with pulmonary nodule found by CT scan.
Receives: Other: Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system

What is being measured

The primary outcome is the main question the study is designed to answer.

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

    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).

    Measured: 3 years

Secondary outcomes (1)

  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.

    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).

    Measured: 3 years

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted24 Jul 2024
  2. Study start30 Jun 2024
  3. Primary completion30 Dec 2026 (estimated)
  4. Study completion30 Jun 2027 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
3,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06518655
Sponsor's protocol ID
LCLN01
Status last verified
Dec 2025
First submitted
19 Jul 2024
Last updated
24 Dec 2025
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.

    PubMed 33538338

  • Xia C, Dong X, Li H, Cao M, Sun D, He S, Yang F, Yan X, Zhang S, Li N, Chen W. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl). 2022 Feb 9;135(5):584-590. doi: 10.1097/CM9.0000000000002108.

    PubMed 35143424

  • Miller KD, Siegel RL, Lin CC, Mariotto AB, Kramer JL, Rowland JH, Stein KD, Alteri R, Jemal A. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016 Jul;66(4):271-89. doi: 10.3322/caac.21349. Epub 2016 Jun 2.

    PubMed 27253694

  • National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.

    PubMed 21714641

  • Shlomi D, Abud M, Liran O, Bar J, Gai-Mor N, Ilouze M, Onn A, Ben-Nun A, Haick H, Peled N. Detection of Lung Cancer and EGFR Mutation by Electronic Nose System. J Thorac Oncol. 2017 Oct;12(10):1544-1551. doi: 10.1016/j.jtho.2017.06.073. Epub 2017 Jul 12.

    PubMed 28709937

  • van de Goor R, van Hooren M, Dingemans AM, Kremer B, Kross K. Training and Validating a Portable Electronic Nose for Lung Cancer Screening. J Thorac Oncol. 2018 May;13(5):676-681. doi: 10.1016/j.jtho.2018.01.024. Epub 2018 Feb 6.

    PubMed 29425703

  • Hanna GB, Boshier PR, Markar SR, Romano A. Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis. JAMA Oncol. 2019 Jan 1;5(1):e182815. doi: 10.1001/jamaoncol.2018.2815. Epub 2019 Jan 10.

    PubMed 30128487

  • Horvath I, Lazar Z, Gyulai N, Kollai M, Losonczy G. Exhaled biomarkers in lung cancer. Eur Respir J. 2009 Jul;34(1):261-75. doi: 10.1183/09031936.00142508.

    PubMed 19567608

  • Mitsui T, Kondo T. Inadequacy of theoretical basis of breath methylated alkane contour for assessing oxidative stress. Clin Chim Acta. 2003 Jul 1;333(1):91; author reply 93-4. doi: 10.1016/s0009-8981(03)00173-6. No abstract available.

    PubMed 12809740

  • Stone BG, Besse TJ, Duane WC, Evans CD, DeMaster EG. Effect of regulating cholesterol biosynthesis on breath isoprene excretion in men. Lipids. 1993 Aug;28(8):705-8. doi: 10.1007/BF02535990.

    PubMed 8377584

  • Nakhleh MK, Amal H, Jeries R, Broza YY, Aboud M, Gharra A, Ivgi H, Khatib S, Badarneh S, Har-Shai L, Glass-Marmor L, Lejbkowicz I, Miller A, Badarny S, Winer R, Finberg J, Cohen-Kaminsky S, Perros F, Montani D, Girerd B, Garcia G, Simonneau G, Nakhoul F, Baram S, Salim R, Hakim M, Gruber M, Ronen O, Marshak T, Doweck I, Nativ O, Bahouth Z, Shi DY, Zhang W, Hua QL, Pan YY, Tao L, Liu H, Karban A, Koifman E, Rainis T, Skapars R, Sivins A, Ancans G, Liepniece-Karele I, Kikuste I, Lasina I, Tolmanis I, Johnson D, Millstone SZ, Fulton J, Wells JW, Wilf LH, Humbert M, Leja M, Peled N, Haick H. Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules. ACS Nano. 2017 Jan 24;11(1):112-125. doi: 10.1021/acsnano.6b04930. Epub 2016 Dec 21.

    PubMed 28000444

  • Zhou J, Huang ZA, Kumar U, Chen DDY. Review of recent developments in determining volatile organic compounds in exhaled breath as biomarkers for lung cancer diagnosis. Anal Chim Acta. 2017 Dec 15;996:1-9. doi: 10.1016/j.aca.2017.09.021. Epub 2017 Sep 13.

    PubMed 29137702

  • Arasaradnam RP, Wicaksono A, O'Brien H, Kocher HM, Covington JA, Crnogorac-Jurcevic T. Noninvasive Diagnosis of Pancreatic Cancer Through Detection of Volatile Organic Compounds in Urine. Gastroenterology. 2018 Feb;154(3):485-487.e1. doi: 10.1053/j.gastro.2017.09.054. Epub 2017 Nov 10. No abstract available.

    PubMed 29129714

  • Chan DK, Zakko L, Visrodia KH, Leggett CL, Lutzke LS, Clemens MA, Allen JD, Anderson MA, Wang KK. Breath Testing for Barrett's Esophagus Using Exhaled Volatile Organic Compound Profiling With an Electronic Nose Device. Gastroenterology. 2017 Jan;152(1):24-26. doi: 10.1053/j.gastro.2016.11.001. Epub 2016 Nov 5. No abstract available.

    PubMed 27825962

  • Gordon SM, Szidon JP, Krotoszynski BK, Gibbons RD, O'Neill HJ. Volatile organic compounds in exhaled air from patients with lung cancer. Clin Chem. 1985 Aug;31(8):1278-82.

    PubMed 4017231

Questions about this trial

What is this clinical trial studying?

An observational study of Pulmonary Nodules, Multiple and Pulmonary Nodules, Solitary, run by ChromX Health at 15 sites in China.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 5 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 24 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 15 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Hengrui Liang, MD (+86 15625064712, hengrui_liang@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

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). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06518655, which also lists 20 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Dec 2025.

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