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Tomography is published by MDPI from Volume 7 Issue 1 (2021). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Grapho, LLC.
Article

Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme

1
IRAT Shared Service, Moffitt Cancer Center, Tampa, FL, USA
2
Department of Diagnostic & Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA
3
Department of Cancer Physiology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, USA
4
Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
5
Mathematical Neuro Oncology Lab., Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, USA
6
Department of Radiology, University of Washington, Seattle, WA, USA
7
Department of Oncologic Sciences, University of S Florida, Tampa, FL 33612, USA
*
Author to whom correspondence should be addressed.
Tomography 2019, 5(1), 135-144; https://doi.org/10.18383/j.tom.2018.00052
Received: 9 December 2018 / Revised: 8 January 2019 / Accepted: 5 February 2019 / Published: 1 March 2019
Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological “habitats” at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct “habitats” based on low- to medium- to high-contrast enhancement and low–high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, p < 0.03; validation cohort, 16 ± 4.0%, p < 0.007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.
Keywords: glioblastoma; survival; MRI; habitats; cancer evolution glioblastoma; survival; MRI; habitats; cancer evolution
MDPI and ACS Style

Stringfield, O.; Arrington, J.A.; Johnston, S.K.; Rognin, N.G.; Peeri, N.C.; Balagurunathan, Y.; Jackson, P.R.; Clark-Swanson, K.R.; Swanson, K.R.; Egan, K.M.; Gatenby, R.A.; Raghunand, N. Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. Tomography 2019, 5, 135-144. https://doi.org/10.18383/j.tom.2018.00052

AMA Style

Stringfield O, Arrington JA, Johnston SK, Rognin NG, Peeri NC, Balagurunathan Y, Jackson PR, Clark-Swanson KR, Swanson KR, Egan KM, Gatenby RA, Raghunand N. Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. Tomography. 2019; 5(1):135-144. https://doi.org/10.18383/j.tom.2018.00052

Chicago/Turabian Style

Stringfield, Olya, John A. Arrington, Sandra K. Johnston, Nicolas G. Rognin, Noah C. Peeri, Yoganand Balagurunathan, Pamela R. Jackson, Kamala R. Clark-Swanson, Kristin R. Swanson, Kathleen M. Egan, Robert A. Gatenby, and Natarajan Raghunand. 2019. "Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme" Tomography 5, no. 1: 135-144. https://doi.org/10.18383/j.tom.2018.00052

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