Imaging of intratumoral heterogeneity in high-grade glioma

Cancer Lett. 2020 May 1;477:97-106. doi: 10.1016/j.canlet.2020.02.025. Epub 2020 Feb 27.

Abstract

High-grade glioma (HGG), and particularly Glioblastoma (GBM), can exhibit pronounced intratumoral heterogeneity that confounds clinical diagnosis and management. While conventional contrast-enhanced MRI lacks the capability to resolve this heterogeneity, advanced MRI techniques and PET imaging offer a spectrum of physiologic and biophysical image features to improve the specificity of imaging diagnoses. Published studies have shown how integrating these advanced techniques can help better define histologically distinct targets for surgical and radiation treatment planning, and help evaluate the regional heterogeneity of tumor recurrence and response assessment following standard adjuvant therapy. Application of texture analysis and machine learning (ML) algorithms has also enabled the emerging field of radiogenomics, which can spatially resolve the regional and genetically distinct subpopulations that coexist within a single GBM tumor. This review focuses on the latest advances in neuro-oncologic imaging and their clinical applications for the assessment of intratumoral heterogeneity.

Keywords: Advanced; Glioblastoma; Glioma; Heterogeneity; Histologic; Imaging; Intratumoral; MRI; Radiogenomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Brain Neoplasms / diagnostic imaging*
  • Brain Neoplasms / genetics
  • Brain Neoplasms / pathology*
  • Brain Neoplasms / therapy
  • Contrast Media
  • Glioma / diagnostic imaging*
  • Glioma / genetics
  • Glioma / pathology*
  • Glioma / therapy
  • Humans
  • Machine Learning
  • Magnetic Resonance Imaging / methods
  • Neoplasm Recurrence, Local / diagnostic imaging
  • Positron-Emission Tomography
  • Therapy, Computer-Assisted

Substances

  • Contrast Media