New method to tell apart benign and malignant lung nodules
Official title: A New Method to Differentiate Benign and Malignant Pulmonary Nodules by Mass Spectrometry Combined With Artificial Intelligence.
Run by China-Japan Friendship Hospital · NCT06056999 · Data updated 2026-11-12
This study is testing a new way to tell if lung nodules are harmless or cancerous by using blood samples and advanced computer analysis to help improve early lung cancer diagnosis.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 150 (estimated) |
| Sponsor | China-Japan Friendship Hospital Academic / other |
| Locations | 1 site (Beijing, Beijing Municipality) |
| Status | Recruiting |
| Started | September 29, 2023 |
| Main results expected | January 2025 |
| Study ends | July 2025 |
| Registry record updated | December 18, 2024 |
| Trial ID | NCT06056999 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults aged 18 and older with pulmonary nodules less than 3 cm that are scheduled for biopsy or surgery.
✕Probably not a fit
Patients with a history of malignant disease or those whose imaging suggests metastasis at other sites may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational clinical trial aims to develop a novel approach for distinguishing between benign and malignant pulmonary nodules using a combination of blood metabolomic analysis and artificial intelligence (AI) image analysis. Participants with suspected malignant nodules will provide peripheral blood samples, which will be analyzed through mass spectrometry to characterize metabolites. The study will categorize nodules based on CT imaging and construct a classification model using machine learning algorithms to enhance diagnostic accuracy. The ultimate goal is to improve early diagnosis of lung cancer by accurately identifying the nature of pulmonary nodules.
Why it matters
Potential benefit: If successful, this method could significantly improve the early diagnosis of lung cancer, leading to better patient outcomes.
How similar studies have gone: While the approach of combining metabolomics and AI for diagnosis is innovative, similar studies have shown promise in improving diagnostic accuracy in other medical fields.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥18 years; * CT imaging shows the presence of pulmonary nodule \<3cm which is scheduled for puncture biopsy or surgery (i.e., the target lesion), the presence of ≥2 target lesions of the same type (categorized by density) are allowed; * Subjects are in good condition with Eastern Cooperative Oncology Group (ECOG) scale of 0-2; * Subjects with fair vital organ function, defined as: white blood cells ≥3.0×10\^9/L, platelets ≥75×10\^9/L, hemoglobin ≥90g/L, alanine aminotransferase and aspartate aminotransferase ≤2.5 times the upper limit of normal values, and serum creatinine \<178μmol/L; * Subjects must have the ability to understand and sign the informed consent in writing voluntarily. Exclusion Criteria: * Imaging examination have suggested the possibility of metastasis at other sites; * ≥2 target lesions with different type categorized by density; * History of malignant disease; * Severe vascular lesions within the last 3 months, or known significant active infection, during acute/chronic tuberculosis infection, or severe cardiovascular and cerebrovascular diseases, dysfunction of liver and renal, or significant endocrine and metabolic disorders, or other serious concomitant diseases that are not controlled; * The specialist/surgeon assessed that puncture or surgery is not available, with contraindication such as coagulation disorders, cardiorespiratory insufficiency, etc.; * History of uncontrolled epilepsy, central nervous system disease, or psychiatric disorders, that may affect the signing of informed consent; * Pregnant or breastfeeding women; * Other conditions deemed by the investigator to be unsuitable for enrollment.
Where it's running
-
China-Japan Friendship Hospital
Beijing, Beijing Municipality, China Recruiting
Study contacts
- Principal investigator: Guangying Zhu — China-Japan Friendship Hospital
- Study coordinator: Guangying Zhu, doctor
- Email: zryyfa@163.com
- Phone: +86-010-84205381
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
-
AI-assisted longitudinal CT to guide indeterminate lung nodules
This trial tests whether giving doctors an AI report that tracks nodules over serial CT scans helps reduce unnecessary benign lung resections in patients with indeterminate nodules.
-
3D airway mapping guides double-lumen tube sizing for thoracic surgery
This study tests whether 3D airway reconstruction helps choose the best double-lumen breathing tube size for adults undergoing thoracic surgery.
-
Intraoperative 3D Longitude-Latitude-Depth Localization vs CT-Guided Lung Localization for Small Peripheral Nodules
This study tests whether intraoperative 3D longitude–latitude–depth localization can identify 0.8–2 cm peripheral lung nodules as reliably as the standard preoperative CT-guided localization in adults undergoing VATS surgery.
-
Making a digital twin of the lung using photon-counting chest CT and clinical data
This project will try to use adults' clinical records and non-contrast photon-counting chest CT scans to find lung nodules, tumors, and other lung diseases and to build a virtual 'digital twin' of the lung.
-
PET scan targeting CDH3 for lung tumors
This will test whether a new PET imaging agent called 68Ga-TOI-1 that targets CDH3 can better detect and stage lung tumors and help tell malignant from benign pulmonary nodules in adults with suspected or confirmed non-small cell lung cancer.
-
Nerve block comparison for CT-guided lung nodule localization: retro‑SCTLB versus TPVB
This trial will try two ultrasound-guided nerve blocks—retro‑SCTLB and thoracic paravertebral block (TPVB)—to see which gives wider local anesthetic spread and sensory numbness for adults having CT‑guided lung nodule localization.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.