Objective: The purpose of this review is to summarize advances in the molecular analysis of gliomas, the role genetics plays in MRI features, and how machine-learning approaches can be used to survey the tumoral environment.
Conclusion: The genetic profile of gliomas influences the course of treatment and clinical outcomes. Though biopsy is the reference standard for determining tumor genetics, it can suffer diagnostic delays due to surgical planning and pathologic assessment. Radiogenomics may allow rapid, low-risk characterization of genetic heterogeneity.
Keywords: glioblastoma; machine learning; radiogenomics.