Supplementary Materials

Supplementary Material for:

Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities

Haruka Itakura, Achal S. Achrol, Lex A. Mitchell, Joshua J. Loya, Tiffany Liu, Erick M. Westbroek, Abdullah H. Feroze, Scott Rodriguez, Sebastian Echegaray, Tej D. Azad, Kristen W. Yeom, Sandy Napel, Daniel L. Rubin, Steven D. Chang, Griffith R. Harsh IV, Olivier Gevaert*

*Corresponding author. E-mail: olivier.gevaert{at}stanford.edu

Published 2 September 2015, Sci. Transl. Med. 7, 303ra139 (2015)
DOI: 10.1126/scitranslmed.aaa7582

This PDF file includes:

  • Methods
  • Fig. S1. Relative contributions of the top 24 imaging features in characterizing each of the clusters.
  • Table S1. Clinical characteristics of the Stanford cohort before and after selection of the development cohort.
  • Table S2. Clinical characteristics of the TCGA cohort before and after selection of the validation cohort.
  • Table S3. All 2D and multislice 2D quantitative MR image features used for analysis.
  • Table S4. Two-dimensional and multislice 2D quantitative MR image features significantly associated with each cluster.
  • Table S5. Cluster assignment by subjects in the development cohort with and without midline-crossing lesions.
  • Table S6. Regulatory signaling pathways significantly associated with each cluster.
  • References (4547)

[Download PDF]