The discrimination of tumor boundaries from normal tissue, as well as the evaluation of tissue heterogeneity and tumor grading often continue to pose a challenge in MRI. Although yielding promising results in various fields of medical imaging, two- dimensional (2D) texture analysis in MRI has, until now, demonstrated a lack of specificity in brain tumor classification. A new three-dimensional (3D) approach using Cooccurrence Matrix analysis is proposed to increase the sensitivity and specificity of brain tumor characterization. A preliminary comparative evaluation of 2D and 3D texture analysis was performed on T(1)-weighted MRI of seven gliomas for characterization of solid tumor, necrosis, edema and surrounding white matter. With 3D compared to 2D method, a better discrimination is obtained between necrosis and solid tumor as well as between edema and solid tumor. Using both methods, peritumoral white matter overlaps with edema, but is completely separated from far homo-lateral matter. This latter shows a complete overlapping with contra-lateral matter. The 3D texture analysis approach could provide a new tool for tumor grading and treatment follow-up, as well as for surgery or radiation therapy planning.