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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 Kim2,6,7, and Sheng-Kwei Song3,4,8

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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