Association between tumor architecture derived from generalized Q-space MRI and survival in glioblastoma

While it is recognized that the overall resistance of glioblastoma to treatment may be related to intra-tumor patterns of structural heterogeneity, imaging methods to assess such patterns remain rudimentary. We utilized a generalized Q-space imaging (GQI) algorithm to analyze magnetic resonance imag...

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Published inOncotarget Vol. 8; no. 26; pp. 41815 - 41826
Main Authors Taylor, Erik N, Ding, Yao, Zhu, Shan, Cheah, Eric, Alexander, Phillip, Lin, Leon, Aninwene, 2nd, George E, Hoffman, Matthew P, Mahajan, Anita, Mohamed, Abdallah S R, McDannold, Nathan, Fuller, Clifton D, Chen, Clark C, Gilbert, Richard J
Format Journal Article
LanguageEnglish
Published United States Impact Journals LLC 27.06.2017
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Summary:While it is recognized that the overall resistance of glioblastoma to treatment may be related to intra-tumor patterns of structural heterogeneity, imaging methods to assess such patterns remain rudimentary. We utilized a generalized Q-space imaging (GQI) algorithm to analyze magnetic resonance imaging (MRI) derived from a rodent model of glioblastoma and 2 clinical datasets to correlate GQI, histology, and survival. In a rodent glioblastoma model, GQI demonstrated a poorly coherent core region, consisting of diffusion tracts <5 mm, surrounded by a shell of highly coherent diffusion tracts, 6-25 mm. Histologically, the core region possessed a high degree of necrosis, whereas the shell consisted of organized sheets of anaplastic cells with elevated mitotic index. These attributes define tumor architecture as the macroscopic organization of variably aligned tumor cells. Applied to MRI data from The Cancer Imaging Atlas (TCGA), the core-shell diffusion tract-length ratio (c/s ratio) correlated linearly with necrosis, which, in turn, was inversely associated with survival (p = 0.00002). We confirmed in an independent cohort of patients (n = 62) that the c/s ratio correlated inversely with survival (p = 0.0004). The analysis of MR images by GQI affords insight into tumor architectural patterns in glioblastoma that correlate with biological heterogeneity and clinical outcome.
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ISSN:1949-2553
1949-2553
DOI:10.18632/oncotarget.16296