AAPM2023_SU-300-IePD-F6-4 Purpose: Traditional methods of evaluating cardiotoxicity rely on cardiac radiation doses and do not incorporate functional imaging. Cardiac functional imaging can improve the ability to provide early prediction for clinical outcomes for lung cancer patients undergoing radiotherapy. FDG-based PET/CT imaging is routinely obtained for staging and disease assessment after treatment. Although FDG PET/CT scans are typically used to evaluate the tumor, studies have shown that the PET cardiac signal is predictive of clinical outcomes. Our study aimed to develop novel functional cardiac delta radiomics using pre and post-treatment FDG PET/CT scans to predict for overall survival (OS). Methods: We conducted a study of 109 lung cancer patients who underwent standard FDG-PET/CT scans pre- and post-radiotherapy. Data from ACRIN 6668 (N=70) and an investigator-initiated lung cancer trial (N=39) for functional avoidance radiotherapy were used. The heart was delineated, and 200 cardiac CT and PET functional radiomics features were selected. Delta radiomics was calculated as the change between pre- and post-PET/CT. The data were divided into 80%/20% training/test set, and feature reduction was performed using Wilcoxon test, hierarchical clustering, and recursive feature elimination. A Gradient Boosting Classifier machine learning model evaluated the ability of the delta PET/CT cardiac radiomics to predict for OS using 10-fold cross-validation for training and area-under-the-curve (AUC) for model assessment. Results: Median survival was 431 days (range 144 to 1640 days). 4 clinically relevant delta features were identified: pre-CT_Maximum, post-CT_Minimum, delta-CT_GLRM_Run_Variance, delta-PET_GLRM_Run_Entropy. The model showed an AUC of 0.91 on the training set and an AUC of 0.87 on the test set. Conclusion: This is the first study to evaluate functional cardiac delta radiomic features from standard PET/CT scans with data showing good predictive AUC for OS. If validated, this work provides automated methods to provide functional cardiac information for clinical outcome prediction in lung cancer patients.