Identifying early progressors following treatment for Glioblastoma (GBM) is paramount in GBM management. MRI-RT platforms provide opportunity for daily MRI of patients. We identified early changes in tumor volume typically starting week 3 or 4 of treatment. We hypothesize tumor volume kinetics are associated with outcome and allow for adapting treatment. We develop a deep learning solution for automatic volume delineation on daily scans, allowing real time monitoring of tumor changes and reducing time burden of segmentation. We obtained DSC for tumor lesion and resection cavity on training and test datasets (mean±standard deviation) 0.87±0.128 and 0.9±0.122; 0.74±0.233 and 0.8±0.277, respectively.