New Method to Differentiate Benign and Malignant Pulmonary Nodules.

Pulmonary Nodules Clinical Trial

Official title:

A New Method to Differentiate Benign and Malignant Pulmonary Nodules by Mass Spectrometry Combined With Artificial Intelligence.

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06056999
• Other study ID #: 2023-KY-0277
• Secondary ID: 2023-NHLHCRF-YYP
• Status: Recruiting
• Start date: September 29, 2023
• Est. completion date: July 2025

Study information

• Verified date: October 2023
• Source: China-Japan Friendship Hospital
• Contact: Guangying Zhu, doctor
• Phone: +86-010-84205381
• Email: zryyfa[@]163.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The goal of this observational clinical trial is to establish a new method for differentiating benign and malignant pulmonary nodules by peripheral blood detection in patients with pulmonary nodules (<3cm). The main questions it aims to answer is: How to combine blood metabolomic mass spectrometry detection and artificial intelligence image analysis to establish a new model for differentiating benign and malignant pulmonary nodules. Participants will be asked provide 4 mL peripheral blood for the test.

Description:

The aim of this clinical trial is to establish a new method for differentiating benign and malignant pulmonary nodules by the combination of metabolomics analysis and artificial intelligence (AI) analysis. It is expected to improve the accuracy of the identification of benign and malignant pulmonary nodules. Patients with clinical suspected malignant pulmonary nodules will be included in this trial. The subjects will be divided into three group by CT image presentation: (1) pure ground-glass nodule (pGGN), (2) part-solid nodule (PSN), (3) solid nodule (SN). Peripheral blood of subjects will be collected and detected by mass spectrometry to obtain the metabolomic characterization. The classification model of each group will be constructed based on the data analysis algorithm by machine learning. The diagnostic efficacy of the new model combined with the AI image analysis system for differentiating benign and malignant pulmonary nodules will be analyzed.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 150
• Est. completion date: July 2025
• Est. primary completion date: January 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Multiple Pulmonary Nodules
• Pulmonary Nodules

Locations

Country	Name	City	State
China	China-Japan Friendship Hospital	Beijing	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
China-Japan Friendship Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Establish an model for differentiating lung nodules.	To establish a new method for differentiating benign and malignant pulmonary nodules by the combination of metabolomics analysis and artificial intelligence (AI) image analysis.	6 months