Lung Cancer
Conditions
Keywords
ctDNA methylation, AI analysis of LDCT images
Brief summary
This topic to take large multicenter study real world, the advanced liquid biopsy will ctDNA methylation detection technique is applied to pulmonary nodules differential diagnosis and early lung cancer screening, validation of early lung cancer screening and diagnosis of molecular classification system model, the feasibility of the development of early lung cancer screening and diagnosis of molecular classification system, improve its early screening early detection accuracy and efficiency, Improve the survival status of lung cancer high-risk population. At the same time, this project combined AI analysis technology of LDCT image results with ctDNA methylation detection, so as to overcome false negatives caused by the deficiency of ctDNA methylation detection technology in sensitivity, specificity, stability and flux, and correct false positive results that may be caused by AI analysis technology of LDCT image results. The combination of the two can avoid missed diagnosis and over - examination and over - treatment.
Detailed description
1. All patients underwent low-dose CT pulmonary nodule AI detection and peripheral blood ctDNA methylation detection at baseline 2. Follow-up plan: Low-risk and medium-risk nodules and some high-risk nodules (5-10mm) were followed up. 10ml peripheral blood was collected from each follow-up and stored for testing until the end of the study. The high-risk nodules over 10mm were evaluated by the expert group and the patients were informed by biopsy or surgical resection. Histopathological diagnosis was made and compared with ctDNA methylation results to analyze the sensitivity and specificity of ctDNA methylation markers of lung cancer. 3. Endpoint: Tissue samples were pathologically diagnosed as benign or malignant.
Interventions
None listed
Sponsors
China-Japan Friendship Hospital
Singlera Genomics Inc.
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
1. Patients with pulmonary nodules confirmed by chest CT are not limited to single nodules; 2. Nodule diameter 5-30mm 3. Nodules include solid, semi-solid and ground glass nodules; 4. Age 18-75, no gender limitation; 5. The newly diagnosed patients did not receive surgery, radiotherapy, chemotherapy, targeted therapy or other tumor-related interventions; 6. Sign informed consent.
Exclusion criteria
1. Patients with diagnosed lung cancer and extrapulmonary malignant tumor; 2. Pulmonary sarcoidosis, pulmonary vasculitis, pulmonary tuberculosis; 3. Patients with poor compliance are expected to be unable to complete follow-up according to the study protocol; 4. Major trauma requiring blood transfusion occurred within one week before enrollment; 5. Pregnant and lactation patients.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To develop a molecular typing system for early screening and diagnosis of lung cancer | assessed up to 36 months | The feasibility of the molecular typing system model for early screening and diagnosis of lung cancer was verified through clinical studies, which significantly improved the accuracy and efficiency of early screening and early diagnosis, and improved the survival status of high-risk population of lung cancer. |
| AI technology was combined with ctDNA methylation detection technology | assessed up to 36 months | In addition to overcoming false negatives caused by deficiencies in sensitivity, specificity, stability and flux of ctDNA methylation detection technology, and correcting false positive results that may be caused by AI, the combination of the two can avoid missed diagnosis, over-examination and over-treatment. |
Countries
China
Contacts
Primary ContactMeng Yang, Bachelor
Backup ContactSinan Wu
Outcome results
None listed