Advanced Densely Connected System with Embedded Spatio-Temporal Features Augmentation for Immunotherapy Assessment

In medical field, the term "immunotherapy" refers to a form of cancer treatment that uses the ability of body's immune system to prevent and destroy cancer cells. In the last few years, immunotherapy has demonstrated to be a very effective treatment in fighting cancer diseases. However, immunotherapy does not work for every patients and moreover, certain types of immunotherapy drugs could have side effects. With this regard, scientific researchers are investigating for effective ways to select the patients who are more likely to respond to the treatment. Hence, pre-clinical data confirmed that, sometimes, the composition of immune system cells infiltrating the tumor micro-environment may interfere with the efficacy of immunotherapy treatments. In this work, we developed a 3D Deep Network with a downstream classifier for selecting and properly augmenting features from chest-abdomen CT images toward improving cancer outcome prediction. In our work, we proposed an effective solution to a specific type of aggressive bladder cancer, called Metastatic Urothelial Carcinoma (mUC). Our experiment results achieved high accuracy confirming the effectiveness of the proposed pipeline.