To find the early biomarkers for predicting the histological grading and prognosis of glioma, the study compared the discriminating efficiency of multiple metrics from DCE, Multi-b DWI and 3D-ASL with a histogram analysis approach, and further evaluated the combined accuracy and the survival association. The accuracy of assessing glioma grading and survival would not significantly improved by a univariate parameter, but highly promoted by combining the multiple parameters of histogram analysis from various MRI modality. We will further utilize the machine learning to evaluate the classifying accuracy.
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