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Updated: May 14, 2026

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
Published on: July 31, 2017
Super-resolution track density imaging of glioblastoma: histopathologic correlation
R F Barajas1, C P Hess, J J Phillips
1Departments of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.
Background And Purpose:
Super-resolution track density imaging generates anatomic images with submillimeter voxel resolution by using high-angular-resolution diffusion imaging and fiber-tractography. TDI within the diseased human brain has not been previously described. The purpose of this study was to correlate TDI with histopathologic features of GBM.
Materials And Methods:
A total of 43 tumor specimens (24 contrast-enhancing, 12 NE, and 7 centrally necrotic regions) were collected from 18 patients with treatment-naïve GBM by use of MR imaging-guided neurosurgical techniques. Immunohistochemical stains were used to evaluate the following histopathologic features: hypoxia, architectural disruption, microvascular hyperplasia, and cellular proliferation. We reconstructed track density maps at a 0.25-mm isotropic spatial resolution by using probabilistic streamline tractography combined with constrained spheric deconvolution (model order, 8; 0.1-mm step size; 1 million seed points). Track density values were obtained from each tissue site. A P value of .05 was considered significant and was adjusted for multiple comparisons by use of the false discovery rate method.
Results:
Track density was not significantly different between contrast-enhancing and NE regions but was more likely to be elevated within regions demonstrating aggressive histopathologic features (P < .05). Significant correlation between relative track density and hypoxia (odds ratio, 3.52; P = .01), architectural disruption (odds ratio, 3.49; P = .03), and cellular proliferation (odds ratio, 1.70; P = .05) was observed irrespective of the presence or absence of contrast enhancement.
Conclusions:
Numeric values of track density correlate with GBM biologic features and may be clinically useful for identification of regions of tumor infiltration within both enhancing and NE components of GBM.

