Semi-automated evaluation of structural characteristics and extension of cerebral gliomas using DTI-MR 3D Texture Analysis

The diffuse and infiltrative growth of cerebral gliomas is a major determinant of poor prognosis. Tumor cells invade surrounding tissues preferentially along white matter tracts, spreading beyond the abnormal area seen on conventional MR images. The detection and characterization of this microscopic infiltration in a non-invasive manner is of outstanding importance for surgical and radiation therapy planning or to assess response to chemotherapy. Diffusion tensor imaging can reveal larger peritumoral abnormalities in gliomas that are not apparent on conventional MR imaging, by detecting the presence of microscopic tumor cells infiltration in white matter around the edge of the gross tumor, as confirmed by image guided biopsies. The aims of this study are: 1) to characterize pathological and healthy tissue in DTI datasets by 3D statistical Texture Analysis, developing a semi-automated segmentation technique of cerebral tumors; 2) to correlate segmentation results with histopathological findings from specimens obtained from image-guided tumor biopsies.