• To quantitatively assess the relationship between lung cancer diagnoses and cardiovascular disease outcomes in the NLST cohort. This aim involves performing statistical analyses to evaluate the incidence and risk of CVD among individuals diagnosed with lung cancer compared to those without, adjusting for relevant covariates.
• To extract and analyze relevant imaging features from LDCT scans that may serve as indicators of cardiovascular risk. This will include the identification and quantification of imaging biomarkers, such as coronary artery calcifications, heart size, and aortic calcifications, which can be automatically detected or measured from LDCT images.
• To develop and validate predictive models that integrate LDCT imaging features and lung cancer diagnosis data for improved CVD screening and risk stratification. The proposed models will leverage both imaging and clinical variables to enhance the accuracy of cardiovascular risk prediction and facilitate the identification of high-risk individuals who may benefit from preventive interventions.
• To evaluate the potential clinical impact and generalizability of using LDCT scans for CVD screening in lung cancer screening populations. This includes assessing the feasibility, added value, and implications for public health if LDCT-based CVD risk assessment were implemented as part of routine screening protocols.

Liang Zhao, Emory University
Yifei Zhang, Emory University