Abstract #0624

Quantitatively Differentiating Multiple Co-Existing Pathologies in High-Grade Glioma

Ze-Zhong Ye¹, Richard Price², Peng Sun³, Ajit George ³, Chunyu Song⁴, Sonika Dahiya⁵, Albert Kim^2,6,7, and Sheng-Kwei Song^3,4,8

¹Chemistry, Washington University, St. Louis, MO, United States, ²Neurological Surgery, Washington University, St. Louis, MO, United States, ³Radiology, Washington University, St. Louis, MO, United States, ⁴Biomedical Engineering, Washington University, St. Louis, MO, United States, ⁵Pathology and Immunology, Washington University, St. Louis, MO, United States, ⁶Neurology, Washington University, St. Louis, MO, United States, ⁷Developmental Biology, Washington University, St. Louis, MO, United States, ⁸Hope Center for Neurological Disorder, Washington University, St. Louis, MO, United States

We demonstrate diffusion MRI histology (D-Histo) is able to detect, differentiate and quantify various co-existing pathologies and structures including tumor, tumor infiltration, necrosis within human brain tumor specimen while conventional MRI and DTI fails. Quantitative maps of H & E and GFAP were generated and co-registered with D-Histo for voxel-wise correlative analysis. D-Histo-derived restricted-isotropic-diffusion fraction correlated with the area of hematoxylin and GFAP positive stain. D-Histo-derived hindered-isotropic-diffusion fraction successfully predicted the distribution of tumor necrosis corresponding with H & E. D-Histo is promising for brain tumor diagnosis, surgical planning, and treatment response monitoring.

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