Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma

Neuroimage Clin. 2016 Mar 12:12:34-40. doi: 10.1016/j.nicl.2016.03.007. eCollection 2016.

Abstract

Background and purpose: In treating glioblastoma (GB), surgical and chemotherapeutic treatment guidelines are, for the most part, independent of tumor location. In this work, we compiled imaging data from a large cohort of GB patients to create statistical atlases illustrating the disease spatial frequency as a function of patient demographics as well as tumor characteristics.

Materials and methods: Two-hundred-six patients with pathology-proven glioblastoma were included. Of those, 65 had pathology-proven recurrence and 113 had molecular subtype and genetic information. We used validated software to segment the tumors in all patients and map them from patient space into a common template. We then created statistical maps that described the spatial location of tumors with respect to demographics and tumor characteristics. We applied a chi-square test to determine whether pattern differences were statistically significant.

Results: The most frequent location for glioblastoma in our patient population is the right temporal lobe. There are statistically significant differences when comparing patterns using demographic data such as gender (p = 0.0006) and age (p = 0.006). Small and large tumors tend to occur in separate locations (p = 0.0007). The tumors tend to occur in different locations according to their molecular subtypes (p < 10(- 6)). The classical subtype tends to spare the frontal lobes, the neural subtype tend to involve the inferior right frontal lobe. Although the sample size is limited, there was a difference in location according to EGFR VIII genotype (p < 10(- 4)), with a right temporal dominance for EFGR VIII negative tumors, and frontal lobe dominance in EGFR VIII positive tumors.

Conclusions: Spatial location of GB is an important factor that correlates with demographic factors and tumor characteristics, which should therefore be considered when evaluating a patient with GB and might assist in personalized treatment.

Keywords: Atlas; Glioblastoma; MRI; Spatial; Statistical.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Atlases as Topic
  • Brain Neoplasms / diagnostic imaging
  • Brain Neoplasms / pathology*
  • Female
  • Glioblastoma / diagnostic imaging
  • Glioblastoma / pathology*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Young Adult