Highlights•Predict treatment response to chemotherapy in lung cancer by using CT images.•Partition CT images into spheres and shells of different radii around the tumor.•Handcrafted and deep-learning-based features from each partition are integrated.•The deep radiomic model achieves an AUC of 0.96 and 0.91 in two datasets.•Simple sphere–shell partition replaces challenging and contentious segmentation.