GBM volumetry using the 3D Slicer medical image computing platform

Sci Rep. 2013:3:1364. doi: 10.1038/srep01364.

Abstract

Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer - a free platform for biomedical research - provides an alternative to this manual slice-by-slice segmentation process, which is significantly faster and requires less user interaction. In this study, 4 physicians segmented GBMs in 10 patients, once using the competitive region-growing based GrowCut segmentation module of Slicer, and once purely by drawing boundaries completely manually on a slice-by-slice basis. Furthermore, we provide a variability analysis for three physicians for 12 GBMs. The time required for GrowCut segmentation was on an average 61% of the time required for a pure manual segmentation. A comparison of Slicer-based segmentation with manual slice-by-slice segmentation resulted in a Dice Similarity Coefficient of 88.43 ± 5.23% and a Hausdorff Distance of 2.32 ± 5.23 mm.

Publication types

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

MeSH terms

  • Glioblastoma / diagnosis*
  • Glioblastoma / pathology
  • Humans
  • Image Processing, Computer-Assisted
  • Imaging, Three-Dimensional*
  • Magnetic Resonance Imaging*
  • Tumor Burden*