Abstract #3222

Spatial habitats features derived from multiparametric MR imaging predict long versus short-term survival in gliomas: Preliminary findings

Hui Ma¹, Zuliwei Ma¹, Shanmei Zeng¹, Mengzhu Wang², Yang Song², Chengxiu Zhang³, Zhiyun Yang¹, and Jing Zhao¹

¹Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, ²MR Scientific Marketing, Siemens Healthineers Ltd., Guangzhou, China, ³Shanghai Key Laboratory of Magneitc Resonance, East China Normal University, Shanghai, China

Synopsis

Keywords: Tumors, Brain, high-grade gliomas, tumor habitats, habitat imagingWe developed spatial habitats based on multiparametric MRI and evaluated associations between features in these habitats and survival time in patients with high-grade gliomas. The voxels in MR images were grouped into 2 clusters using the K-means clustering algorithm of in-house software nnFAE (V.0.0.10). Structural MRI habitats were defined on CE-T1WI and T2-Flair images, and physiologic MRI habitats were defined on MK derived from DKI and Ktrans derived from DCE imaging. Results showed physiologic habitats weighed more than structural ones, and suggested low vascular-permeability-and-tissue-complexity habitats may play an important role in distinguishing long- and short-term survival of high-grade gliomas patients.

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