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Optimization of Lung Cancer Screening Based on Multicenter Data

Principal Investigator
Name
xinyue shan
Degrees
Undergraduate
Institution
Beijing Wuzi University
Position Title
student
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-1302
Initial CDAS Request Approval
Jul 26, 2024
Title
Optimization of Lung Cancer Screening Based on Multicenter Data
Summary
This project aims to assess and optimize the effectiveness of lung cancer screening methods using a comprehensive multicenter dataset from the United States. By comparing the results of CT scans and chest X-rays (CXR), we seek to determine whether CT scanning significantly reduces lung cancer mortality in high-risk populations. The project involves extensive patient data and image analysis, covering clinical information and imaging data from approximately 53,454 participants. The ultimate goal is to improve screening strategies, enabling earlier detection of lung cancer and increasing patient survival rates.
Aims

Data Integration and Cleaning: Collect, organize, and clean data from the LSS and ACRIN projects, including patient information, imaging data, and diagnostic and treatment records.
Comparison of Screening Methods: Analyze the detection results of CT scans and CXRs to evaluate their sensitivity and specificity in lung cancer screening and assess their impact on lung cancer mortality.
Image Data Processing: Develop and apply advanced imaging analysis algorithms for lung nodule detection and segmentation on CT and CXR images to improve the accuracy of cancer screening.
Clinical Application Models: Build predictive models based on data and image analysis to help identify high-risk individuals and tailor personalized screening strategies.
Privacy and Ethical Compliance: Ensure all data processing and analysis procedures comply with privacy and ethical standards, protecting patient personal information.

Collaborators

Wuzi