Currently, in diffuse glioma, in addition to histopathology, the molecular features have an important role in glioma diagnosis. As a new computing framework for diffusion spectrum imaging (DSI), mean apparent propagator (MAP) could investigate more subtle information of tumor microstructures than the Gaussian diffusion models, while MAP has not been studied much in glioma. Besides, the analysis of tumor habitat could reflect the glioma heterogeneity. Hence, we aim to analyze the tumor habitat-derived MAP metrics and further explore their clinical value in glioma evaluation, meanwhile, we introduce Diffusion-kurtosis imaging (DKI) as a reference to compare the diagnostic efficiency of DSI.
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Zeng et al. (2024) studied this question.
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