Abstract
BACKGROUND AND PURPOSE: MR imaging tractography is increasingly used to perform noninvasive presurgical planning for brain gliomas. Recently, constrained spherical deconvolution tractography was shown to overcome several limitations of commonly used DTI tractography. The purpose of our study was to evaluate WM tract alterations of both the corticospinal tract and arcuate fasciculus in patients with high-grade gliomas, through qualitative and quantitative analysis of probabilistic constrained spherical deconvolution tractography, to perform reliable presurgical planning. MATERIALS AND METHODS: Twenty patients with frontoparietal high-grade gliomas were recruited and evaluated by using a 3T MR imaging scanner with both morphologic and diffusion sequences (60 diffusion directions). We performed probabilistic constrained spherical deconvolution tractography and tract quantification following diffusion tensor parameters: fractional anisotropy; mean diffusivity; linear, planar, and spherical coefficients. RESULTS: In all patients, we obtained tractographic reconstructions of the medial and lateral portions of the corticospinal tract and arcuate fasciculus, both on the glioma-affected and nonaffected sides of the brain. The affected lateral corticospinal tract and the arcuate fasciculus showed decreased fractional anisotropy (z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) and linear coefficient (z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) along with increased spherical coefficient (z = -2.51, n = 20, P = .006; z = -2.52, n = 20, P = .006). Mean diffusivity values were increased only in the lateral corticospinal tract (z = -2.53, n = 20, P = .006). CONCLUSIONS: In this study, we demonstrated that probabilistic constrained spherical deconvolution can provide essential qualitative and quantitative information in presurgical planning, which was not otherwise achievable with DTI. These findings can have important implications for the surgical approach and postoperative outcome in patients with glioma.