Certain aspects of radiomics and radiogenomics in glioblastoma: what the images hide?

Abstract

Radiogenomics is a novel and promising field connecting a variety of imaging possibilities with various genomic events. Advances in genomics provided by the Cancer Genome Atlas and Human Genome projects made it possible to integrate this information with imaging phenotypes of malignant brain tumors for a more detailed understanding of their biology. Radiomics, in turn, lies at the intersection of radiology, computer science and mathematical statistics. Unlike radiogenomics, it does not focus on the specific relationship between the radiophenotype and tumor genotype, but rather identifies the analysis methodology. With its help, quantitative features are extracted from medical images, establishing patient’s genotype-phenotype correlation. This contributes to the risk stratification and patient management. The article discusses some topical aspects of radiomics and radiogenomics of glioblastomas and their application in neurooncology.Previously, several groups of researchers showed the relationship between visualization features of glioblastomas and the prognosis of the course of the disease.One of the modern problems of radiomics is the search for imaging features that can serve as key prognostic markers for risk stratification of patients with glioblastomas using machine learning tools.Thus, the prospects for the development of radiomics and radiogenomics methods include predicting patient survival, differential diagnosis of glioblastomas, determining the degree of malignancy, identifying mutations and amplifications, detecting tumor progression, pseudoprogression, etc.