Diffusion Tensor MR Imaging of Cerebral Gliomas: Evaluating Fractional Anisotropy Characteristics

Abstract

BACKGROUND AND PURPOSE: FA correlation to glioma tumor grade has been mixed if not disappointing. There are several potential underlying fundamental issues that have contributed to these results. In an attempt to overcome these past shortfalls, we evaluated characteristics of FA of the solid tissue components of gliomas, including whether high-grade gliomas have a greater variation of FA than low-grade gliomas.

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

“…Unfortunately, promising metrics such as diffusional kurtosis, p:q diffusion tensor decomposition, and maximum SD of FA were provided in too few studies to be accessible by meta-analysis. 19,36,37 Considerable heterogeneity was observed in the cohort of studies for some of the metrics we tested. One source of heterogeneity was sampling error in pathologic specimens used for histologic grading.…”

“…[4][5][6][7][8][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][11][12][13][14][15][16][17][18][19][20][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.…”

Differentiation of Tumefactive Demyelinating Lesions from High-Grade Gliomas with the Use of Diffusion Tensor Imaging

“…Although the causes of these hyperintensities in high-grade gliomas are not known, their presence had been reported in previous studies. 15,[25][26][27] We speculate that these hyperintensities may represent tumor parts with focal high cellularity. 13 On visual inspection, the perilesional hyperintense FA rim is the most sensitive, specific, and accurate sign in differentiating TDLs from high-grade gliomas.…”

Texture analysis on diffusion tensor imaging: discriminating glioblastoma from single brain metastasis

“…We predicted this irregularity by calculating the entropy derived from ADC maps in the peritumoral edema to differentiate GBM from MET across the different filters, with a sensitivity and specificity of 77% and 95%, respectively and a corresponding AUC of 0.89. White et al (11) reported that FA is mainly affected by tumor infiltration, where destruction of nerve fibers is represented as anisotropy. Experimental studies have shown that GBM cells produce tumor-specific extracellular matrix components leading to high anisotropy and consequently high FA values.…”

“…From this the amount of destruction of nerve fibers, which can occur secondary to tumor infiltration, can be displayed in constructed maps such as fractional anisotropy (FA) and apparent diffusion coefficient (ADC) (11,12).…”