Abstract #2115

Texture analysis of mean apparent propagator-magnetic resonance imaging in distinguishing glioblastoma and solitary brain metastasis

Guohua Zhao¹, Yizhou Su², Yusong Lin², Jie Dong³, Eryuan Gao¹, Xiaoyue Ma¹, Jie Bai¹, Huiting Zhang⁴, Xu Yan⁴, Guang Yang⁵, and Jingliang Cheng¹

¹The Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, ²Collaborative Innovation Center for Internet Healthcare, Zhengzhou, China, ³School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, China, ⁴MR Scientific Marketing, Siemens Healthineers, Shanghai, China, ⁵Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China

Synopsis

Keywords: Tumors, Diffusion/other diffusion imaging techniquesPreoperative differentiation between glioblastomas (GBM) and solitary brain metastases (SBM) would aid in appropriate treatment planning and follow-up. Mean apparent propagator (MAP) MRI is effective in evaluating the inhomogeneity of brain microstructure. Texture analysis can be used to extract and quantify these inhomogeneities. In this study, we extracted the texture features from MAP-MRI, and validated the candidate features in discriminating between GBM and SBM. The RTAP model achieved the best discriminative power for the single metric model, and performed similarly to the MAP-MRI combined model. Texture analysis based on MAP-MRI has great potential to distinguish between the two entities.

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