Purpose: To seek to distinguish and visualize the different magnetic resonance imaging (MRI) growth patterns among malignant gliomas utilizing visually enhanced diffusion tensor imaging (DTI).
Materials and Methods:Nineteen consecutive patients undergoing image-guided resection of a newly diagnosed malignant glioma underwent add-on acquisition of DTI data based on an Institutional Review Board (IRB)-approved imaging protocol during preoperative MRI scans for routine intraoperative image guidance. Tumor growth patterns were assigned to expansive or mixed/infiltrative classes as described in the companion article (24). Infiltrating tumors were WHO Grade IV astrocytomas and all expansive tumors were either WHO Grade III astrocytomas or WHO Grade II astrocytomas. DTI-based white matter tractography was conducted and the DTI data were fused with anatomical images using an in-house software package we developed to enhance the visualization of the tumor/fiber interface. In one case additional analysis was performed with 2D multivoxel 1 H-MRSI utilizing a 2D chemical shift imaging (CSI) technique to corroborate the nature of this interface.Results: Out of the 19 tumor patients studied, 11 had infiltrative tumors and the other 8 had expansive tumors. While less clear with 2D axial diffusion color maps, visually enhanced 3D reconstructions of the tumor/fiber interface successfully corroborated distinctive growth patterns. This was particularly evident when viewed in 3D video loops of each tumor/fiber interface.
Conclusion:We have successfully developed software that visually enhances the anatomic details of the tumor/fiber interface in patients with anaplastic astrocytomas. These data support the existence of a subgroup of patients within the WHO Grade III classification with expansive tumors and a significantly better prognosis. DIFFUSION TENSOR IMAGING (DTI) can depict diffusivity and diffusion directionality of water molecules and allows for mapping white matter tracts in the brain (1-3). There has been strong interest in exploring the clinical applications of DTI, including assessment of brain tumors (4 -8). These studies mainly explored the use of quantitative diffusion measures (i.e., mean diffusivity, fractional anisotropy) derived from DTI. In our study we focused on distinguishing different tumor growth patterns by using visually enhanced DTI-based tractography to visualize the tumor/fiber interface in patients with anaplastic astrocytomas. To this end, novel DTI visualization techniques were developed in the form of user-friendly features in an in-house software that we describe herein.Many approaches have been investigated to assist in the visualization of DTI information. The simplest way was to display the DTI data projected onto 2D slices. The direction of the primary eigenvector was first projected onto a 2D plane, then color-coded, usually by mapping x, y, z components to RGB (red, green, and blue) (9,10). The brightness of such color maps are usually modulated by fractional anisotropy (FA). This method ca...