Meta-Analysis of Diffusion Metrics for the Prediction of Tumor Grade in Gliomas

BACKGROUND AND PURPOSE:Diffusion tensor metrics are potential in vivo quantitative neuroimaging biomarkers for the characterization of brain tumor subtype. This meta-analysis analyzes the ability of mean diffusivity and fractional anisotropy to distinguish low-grade from high-grade gliomas in the identifiable tumor core and the region of peripheral edema.MATERIALS AND METHODS:A meta-analysis of articles with mean diffusivity and fractional anisotropy data for World Health Organization low-grade (I, II) and high-grade (III, IV) gliomas, between 2000 and 2013, was performed. Pooled data were analyzed by using the odds ratio and mean difference. Receiver operating characteristic analysis was performed for patient-level data.RESULTS:The minimum mean diffusivity of high-grade gliomas was decreased compared with low-grade gliomas. High-grade gliomas had decreased average mean diffusivity values compared with low-grade gliomas in the tumor core and increased average mean diffusivity values in the peripheral region. High-grade gliomas had increased FA values compared with low-grade gliomas in the tumor core, decreased values in the peripheral region, and a decreased fractional anisotropy difference between the tumor core and peripheral region.CONCLUSIONS:The minimum mean diffusivity differs significantly with respect to the World Health Organization grade of gliomas. Statistically significant effects of tumor grade on average mean diffusivity and fractional anisotropy were observed, supporting the concept that high-grade tumors are more destructive and infiltrative than low-grade tumors. Considerable heterogeneity within the literature may be due to systematic factors in addition to underlying lesion heterogeneity.

Diffusion tensor imaging is an MR imaging technique that can quantify diffusion of water in the brain and characterize the structural integrity of white matter tracts.^1–3 Multiple studies have examined the ability of basic diffusion tensor metrics such as mean diffusivity (MD) or the apparent diffusion coefficient and fractional anisotropy (FA) to discriminate the tumor grade of gliomas. Disruption of normal white matter structural integrity by primary glial neoplasms should theoretically reduce fractional anisotropy and increase mean diffusivity.Mean diffusivity is positively correlated with decreased tumor cellular density and increased patient survival, and significant effects are reported in several studies with respect to discriminating tumor grade specifically by using minimum mean diffusivity (minMD).^4–9 In contradistinction, there is no definitive consensus on the ability of fractional anisotropy to assess tumor grade, cellular density, and parenchymal infiltration or to prognosticate patient survival.^7,10–21 We performed a quantitative meta-analysis of the existing literature to determine the statistical consensus of mean diffusivity and fractional anisotropy in distinguishing tumor grade of gliomas, separately examining the identifiable tumor core and region of peripheral signal abnormality.