Radiomics is the method of choice for investigating the association between cancer imaging
phenotype, cancer genotype and clinical outcome prediction in the era of precision …

Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays
an essential role in each phase of lung cancer management, from detection to assessment …

Purpose Many radiomics features were originally developed for non‐medical imaging
applications and therefore original assumptions may need to be reexamined. In this study …

Radiomics (radiogenomics) characterizes tumor phenotypes based on quantitative image
features derived from routine radiologic imaging to improve cancer diagnosis, prognosis …

Background In this study we retrospectively evaluated the capability of computed
tomography (CT)-based radiomic features to predict epidermal growth factor receptor …

Objectives To assess the association between CT features and EGFR, ALK, KRAS mutations
in non-small cell lung cancer. Methods Patients undergoing chest CT and testing for the …

Purpose: Using standard-of-care CT images obtained from patients with a diagnosis of non–
small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of …

Medical imaging plays a fundamental role in oncology and drug development, by providing
a non-invasive method to visualize tumor phenotype. Radiomics can quantify this phenotype …

Purpose To retrospectively identify the relationship between epidermal growth factor
receptor (EGFR) mutation status, predominant histologic subtype, and computed …

Purpose To create a radiogenomic map linking computed tomographic (CT) image features
and gene expression profiles generated by RNA sequencing for patients with non–small cell …