Abstract #3950

Feature decomposition based examining tumor heterogenity on dynamic susceptibility contrast enhansed MRI data

Bing Ji¹, Silun Wang¹, Liya Wang^1,2, Xiaofeng Yang³, and Hui Mao¹

¹Department of Radiology and Imaging Sciences, Emory University School of Medicine, Emory University, Atlanta, GA, United States, ²Long Hua Hospital, Guangdong, China, ³Department of Radiation Oncology, Emory University School of Medicine, Emory University, Atlanta, GA, United States

Dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC MRI) is widely used for studying blood perfusion in brain tumors. We report use of a model free approach combining with a feature extraction strategy to interrogate time course data from DSC MRI of brain tumor patients. The results reveal the spatial and temporal heterogenity of brain tumors based on features of time course profiles. The number of features/patterns in DSC data indicating the heterogenity of the tumor is associated with the tumor grade. The new method can potentially extract more tumor physiology information from DSC MRI comparing to the traditional model-based analysis.

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