Enhancing the utility of these methods with tractography DTI has been used to predict surgical outcome from the patterns exhibited by co-aligned neural fibers and to assess brain connectivity. Current methods of DW-MRI analysis are generally based on diffusion tensor imaging (DTI) algorithms that depict tumor organization through net cellular orientation (fractional anisotropy, FA) or regional cellularity (apparent diffusion coefficient, ADC). In so doing, we defined a novel macroscopic feature of glioblastoma, that is, intra-tumor variability of alignment that appears to correlate with regional differences of necrosis and anticipates clinical performance.ĭiffusion-weighted magnetic resonance imaging (DW-MRI) has been employed to assess various tumor features and predict clinical outcome. We applied herein an image analysis algorithm, termed generalized Q-space imaging (GQI), to determine whether regional patterns of glioblastoma tissue organization could be derived non-invasively, and whether such patterns are substantially related to the underlying tumor biology and clinical outcome. The tumor was originally termed glioblastoma multiforme because of the variegated appearance of white, hyper-cellular regions interwoven with regions of yellow necrotic tissues, zones of hemorrhagic tissues, and cystic areas. One of the most notable features of glioblastoma is the significant degree of regional biological heterogeneity apparent on pathological inspection. It remains one of the deadliest of human cancers, with median survival of approximately 14 months. Glioblastoma is the most common form of adult primary malignant brain tumor. Conclusions: The analysis of MR images by GQI affords insight into tumor architectural patterns in glioblastoma that correlate with biological heterogeneity and clinical outcome. We confirmed in an independent cohort of patients ( n = 62) that the c/s ratio correlated inversely with survival ( p = 0.0004). Applied to MRI data from The Cancer Imaging Atlas (TCGA), the core-shell diffusion tract-length ratio (c/s ratio) correlated linearly with necrosis, which, in turn, was inversely associated with survival ( p = 0.00002). These attributes define tumor architecture as the macroscopic organization of variably aligned tumor cells.

Histologically, the core region possessed a high degree of necrosis, whereas the shell consisted of organized sheets of anaplastic cells with elevated mitotic index.

Results: In a rodent glioblastoma model, GQI demonstrated a poorly coherent core region, consisting of diffusion tracts <5 mm, surrounded by a shell of highly coherent diffusion tracts, 6-25 mm. Methods: We utilized a generalized Q-space imaging (GQI) algorithm to analyze magnetic resonance imaging (MRI) derived from a rodent model of glioblastoma and 2 clinical datasets to correlate GQI, histology, and survival. While it is recognized that the overall resistance of glioblastoma to treatment may be related to intra-tumor patterns of structural heterogeneity, imaging methods to assess such patterns remain rudimentary.

Qspace architecture