In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature

Neuro Oncol. 2018 Jul 5;20(8):1068-1079. doi: 10.1093/neuonc/noy033.

Abstract

Background: Epidermal growth factor receptor variant III (EGFRvIII) is a driver mutation and potential therapeutic target in glioblastoma. Non-invasive in vivo EGFRvIII determination, using clinically acquired multiparametric MRI sequences, could assist in assessing spatial heterogeneity related to EGFRvIII, currently not captured via single-specimen analyses. We hypothesize that integration of subtle, yet distinctive, quantitative imaging/radiomic patterns using machine learning may lead to non-invasively determining molecular characteristics, and particularly the EGFRvIII mutation.

Methods: We integrated diverse imaging features, including the tumor's spatial distribution pattern, via support vector machines, to construct an imaging signature of EGFRvIII. This signature was evaluated in independent discovery (n = 75) and replication (n = 54) cohorts of de novo glioblastoma, and compared with the EGFRvIII status obtained through an assay based on next-generation sequencing.

Results: The cross-validated accuracy of the EGFRvIII signature in classifying the mutation status in individual patients of the independent discovery and replication cohorts was 85.3% (specificity = 86.3%, sensitivity = 83.3%, area under the curve [AUC] = 0.85) and 87% (specificity = 90%, sensitivity = 78.6%, AUC = 0.86), respectively. The signature was consistent with EGFRvIII+ tumors having increased neovascularization and cell density, as well as a distinctive spatial pattern involving relatively more frontal and parietal regions compared with EGFRvIII- tumors.

Conclusions: An imaging signature of EGFRvIII was found, revealing a complex, yet distinct macroscopic glioblastoma phenotype. By non-invasively capturing the tumor in its entirety, the proposed methodology can assist in evaluating the tumor's spatial heterogeneity, hence overcoming common spatial sampling limitations of tissue-based analyses. This signature can preoperatively stratify patients for EGFRvIII-targeted therapies, and potentially monitor dynamic mutational changes during treatment.

Publication types

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

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor / genetics*
  • Brain Neoplasms / genetics*
  • Brain Neoplasms / pathology
  • Cohort Studies
  • Diffusion Tensor Imaging / methods*
  • ErbB Receptors / genetics*
  • Female
  • Follow-Up Studies
  • Glioblastoma / genetics*
  • Glioblastoma / pathology
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Mutation*
  • Prognosis
  • Young Adult

Substances

  • Biomarkers, Tumor
  • epidermal growth factor receptor VIII
  • ErbB Receptors