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We 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.
Ma et al. (Wed,) studied this question.