Gliomas are the most common primary tumors of the central nervous system. As surgical biopsy may not be always feasible, an accurate noninvasive glioma grading is highly desirable for planning treatments. Recently, a number of non-Gaussian diffusion models were developed to characterize the anomalous diffusion behavior of the complex biological tissue. Among these, the continuous-time random walk (CTRW) model showed a great potential to probe the tissue heterogeneity and complexity that is elevated with tumor progression. In this study, we show that the CTRW parameters are capable of differentiating glioma grades, beyond simply separating low-grade and high-grade as in many diffusion MR studies on gliomas.
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