Progress in the Application of Energy-spectrum CT Imaging and Radiomics for the Diagnosis of Lung Cancer and Subtype Differentiation

Abstract

Lung cancer is the most prevalent malignancy and a serious threat to human health, and the early non-invasive diagnosis of lung cancer has been a hot topic of research in recent years. Lung cancer is subtyped into small cell lung cancer and non-small cell lung cancer, which is closely related to long-term smoking exposure history and chronic lung diseases, and its subtypes are inseparable from the diagnosis and prognosis of lung cancer. With the iterative development of CT technology, energy spectrum CT has been applied. Energy spectral CT of lung cancer can reduce artifacts, improve signal-to-noise ratio and clarity of images, and provide more information for CT diagnosis of lung cancer by combining multi-parameter energy spectral data at the same time. Radiomics refers to the acquisition of a large number of imaging histological features from other imaging images such as CT, ultrasound and MR, and the selection of valuable imaging histological clinical data for analysis. The exploration of disease by energy-spectrum CT combined with radiomics is a hot spot and trend in current research, and this paper will review the research progress of both on lung cancer subtypes.