Mut-Detecter: An EGFR activating mutation type classification method with a deep convolutional neural network

Epidermal growth factor receptor (EGFR) plays an essential role in tumor cell proliferation, angiogenesis and apoptosis inhibition; it is a crucial factor leading to cancer occurrence. For example, EGFR tyrosine kinase inhibitors in treating lung cancer patients have an excellent therapeutic effect. Targeted therapy based on EGFR gene mutation is one of the mainstream lung cancer treatment methods. Recent studies have shown that pulmonary nodules’ characteristics are associated with the mutant status of EGFR, which provides the possibility of using CT images of patients with pulmonary nodules to predict the mutant status of EGFR. This study used the deep learning algorithm to establish the EGFR mutation type prediction model based on CT image recognition. The data sets used for model training and testing included 121 labeled CT images from hospital patients with pulmonary nodules. The research results showed that the model could be used for the non-invasive EGFR mutation type based on CT images.