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Abstract #3215

3D Texture Analysis of Quantitative Susceptibility Mapping distinguishes Anaplastic Astrocytoma from Glioblastoma 

Jinwei Zhang1, Shun Zhang2, Hersh Patel3, Jacquelyn Knapp4, Gloria Chiang2, David Pisapia2, John Tsiouris2, Linda Heier2, Pascal Spincemaille2, Thanh Nguyen2, Yi Wang2, and Ilhami Kovanlikaya2
1Biomedical Engineering, Cornell University, Ithaca, NY, United States, 2Radiology, Weill Cornell Medical College, New York, NY, United States, 3New York Presbyterian Hospital, New York, NY, United States, 4Cornell University, New York, NY, United States

3D texture analysis-based feature extraction was deployed on QSM images of malignant astrocytoma (Anaplastic Astrocytoma (AA), grade III and Glioblastoma (GB), grade IV) and support vector classifier (SVC) (1) was trained and tested on multiple training-test dataset splits with different numbers of selected features using cross-validation (CV). Experiments indicate texture analysis on QSM is useful for differentiating AA and GB with high accuracy (94.7%).

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