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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