# Radiogenomics of Glioblastoma: Identification of Radiomics associated with Molecular Subtypes

arXiv: https://arxiv.org/abs/2010.14068 · HTML: https://mlsanity.com/paper/2010.14068/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Oct 2020.

## Built on by (most cited first, 2 of 2)

- [Glioblastoma Multiforme Prognosis: MRI Missing Modality Generation, Segmentation and Radiogenomic Survival Prediction](https://mlsanity.com/paper/2104.01149/) (2021)
- [Future Artificial Intelligence tools and perspectives in medicine](https://mlsanity.com/paper/2206.03289/) (2022)

## Abstract (arXiv)

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% utilizing radiomics and accuracy over 90% utilizing gene expression profiles.