Fig. 1
Experimental design. FMCIB, with a 3D ResNet50 backbone and pre-trained on more than 11,000 lesions, is used in this study10. The foundation model is used on both pre-treatment and post-treatment CT scans to extract 4096-D feature vectors. The post-treatment feature vector is element-wise subtracted from the pre-treatment feature vector resulting in a single 4096-D vector. The element-wise subtraction vector is used to calculate a Euclidean distance that is passed along as a feature to a random forest clinical model and a Cox proportional hazards model. The element-wise subtracted vector alongside the feature vectors of the pre-treatment and post-treatment scans are also passed to a gradient boosting survival model.
