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Multicenter Study
. 2015 Nov;17(11):1525-37.
doi: 10.1093/neuonc/nov117. Epub 2015 Jul 22.

Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival

Pattana Wangaryattawanich  1 , Masumeh Hatami  1 , Jixin Wang  1 , Ginu Thomas  1 , Adam Flanders  1 , Justin Kirby  1 , Max Wintermark  1 , Erich S Huang  1 , Ali Shojaee Bakhtiari  1 , Markus M Luedi  1 , Syed S Hashmi  1 , Daniel L Rubin  1 , James Y Chen  1 , Scott N Hwang  1 , John Freymann  1 , Chad A Holder  1 , Pascal O Zinn  1 , Rivka R Colen  1
Affiliations
Multicenter Study

Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival

Pattana Wangaryattawanich et al. Neuro Oncol. 2015 Nov.

Abstract

Background: Despite an aggressive therapeutic approach, the prognosis for most patients with glioblastoma (GBM) remains poor. The aim of this study was to determine the significance of preoperative MRI variables, both quantitative and qualitative, with regard to overall and progression-free survival in GBM.

Methods: We retrospectively identified 94 untreated GBM patients from the Cancer Imaging Archive who had pretreatment MRI and corresponding patient outcomes and clinical information in The Cancer Genome Atlas. Qualitative imaging assessments were based on the Visually Accessible Rembrandt Images feature-set criteria. Volumetric parameters were obtained of the specific tumor components: contrast enhancement, necrosis, and edema/invasion. Cox regression was used to assess prognostic and survival significance of each image.

Results: Univariable Cox regression analysis demonstrated 10 imaging features and 2 clinical variables to be significantly associated with overall survival. Multivariable Cox regression analysis showed that tumor-enhancing volume (P = .03) and eloquent brain involvement (P < .001) were independent prognostic indicators of overall survival. In the multivariable Cox analysis of the volumetric features, the edema/invasion volume of more than 85 000 mm(3) and the proportion of enhancing tumor were significantly correlated with higher mortality (Ps = .004 and .003, respectively).

Conclusions: Preoperative MRI parameters have a significant prognostic role in predicting survival in patients with GBM, thus making them useful for patient stratification and endpoint biomarkers in clinical trials.

Keywords: TCGA; glioblastoma; imaging; overall survival; progression free survival.

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Figures

Fig. 1.
Fig. 1.
A 51-year-old female patient with right frontoparietal GBM. Representative case of tumor segmentation. (A) Axial FLAIR image shows segmentation of the FLAIR hyperintensity region defined as edema/tumor invasion (blue) (B) Axial postcontrast T1WI demonstrates segmentation of the enhancing tumor (yellow) and area of necrosis (orange). (C) Label map image demonstrating the segmented tumor.
Fig. 2.
Fig. 2.
Overall survival in patients with GBM stratified by (A) volume of edema/tumor invasion; (B) volume of enhancing tumor; (C) proportion of volume of enhancing tumor; (D) age; (E) KPS; (F) major axis based on VASARI feature set; (G) T1/FLAIR ratio; (H) distribution/focality; (I) enhancement across the midline; (J) deep white matter invasion; (K) ependymal extension.
Fig. 2.
Fig. 2.
Overall survival in patients with GBM stratified by (A) volume of edema/tumor invasion; (B) volume of enhancing tumor; (C) proportion of volume of enhancing tumor; (D) age; (E) KPS; (F) major axis based on VASARI feature set; (G) T1/FLAIR ratio; (H) distribution/focality; (I) enhancement across the midline; (J) deep white matter invasion; (K) ependymal extension.
Fig. 3.
Fig. 3.
Progression-free survival in patients with GBM stratified by (A) volume of edema/tumor invasion; (B) major axis; (C) T1/FLAIR ratio; (D) distribution/focality; (E) enhancement across the midline; (F) nonenhancing tumor across the midline; (G) deep white matter invasion; (H) ependymal extension.
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