Radiogenomics of Glioblastoma: Identification of Radiomics associated with Molecular Subtypes

by   Navodini Wijethilake, et al.

Glioblastoma is the most malignant type of central nervous system tumor with GBM subtypes cleaved based on molecular level gene alterations. These alterations are also happened to affect the histology. Thus, it can cause visible changes in images, such as enhancement and edema development. In this study, we extract intensity, volume, and texture features from the tumor subregions to identify the correlations with gene expression features and overall survival. Consequently, we utilize the radiomics to find associations with the subtypes of glioblastoma. Accordingly, the fractal dimensions of the whole tumor, tumor core, and necrosis regions show a significant difference between the Proneural, Classical and Mesenchymal subtypes. Additionally, the subtypes of GBM are predicted with an average accuracy of 79 radiomics and accuracy over 90


page 1

page 2

page 3

page 4


RADIOHEAD: Radiogenomic Analysis Incorporating Tumor Heterogeneity in Imaging Through Densities

Recent technological advancements have enabled detailed investigation of...

Biologic and Prognostic Feature scores from Whole-Slide Histology Images Using Deep Learning

Histopathology is a reflection of the molecular changes and provides pro...

Fluorescence molecular optomic signatures improve identification of tumors in head and neck specimens

In this study, a radiomics approach was extended to optical fluorescence...

Inverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition

Sparse representation based classification (SRC) methods have achieved r...

Please sign up or login with your details

Forgot password? Click here to reset