Experimental Texture Analysis in Glioblastoma: A Methodological Study

Invest Radiol. 2017 Jun;52(6):367-373. doi: 10.1097/RLI.0000000000000354.

Abstract

Objectives: Analysis of a single slice of a tumor to extract biomarkers for texture analysis may result in loss of information. We investigated correlation of fractional volumes to entire tumor volumes and introduced expanded regions of interest (ROIs) outside the visual tumor borders in glioblastoma.

Materials and methods: Retrospective slice-by-slice volumetric texture analysis on 46 brain magnetic resonance imaging subjects with histologically confirmed glioblastoma was performed. Fractional volumes were analyzed for correlation to total volume. Expanded ROIs were analyzed for significant differences to conservative ROIs.

Results: As fractional tumor volumes increased, correlation with total volume values for mean, SD, mean of positive pixels, skewness, and kurtosis increased. Expanding ROI by 2 mm resulted in significant differences in all textural values.

Conclusions: Fractional volumes may provide an optimal trade-off for texture analysis in the clinical setting. All texture parameters proved significantly different with minimal expansion of the ROI, underlining the susceptibility of texture analysis to generating misrepresentative tumor information.

MeSH terms

  • Adult
  • Brain / diagnostic imaging
  • Brain / pathology
  • Brain Neoplasms / diagnostic imaging*
  • Brain Neoplasms / pathology*
  • Female
  • Glioblastoma / diagnostic imaging*
  • Glioblastoma / pathology*
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Male
  • Retrospective Studies
  • Tumor Burden