Aim:Background: Accurate preoperative grading and isocitrate dehydrogenase (IDH) identification is highly important for proper treatment planning and prognosis evaluation in glioma patients. Purpose To explore the applicability of histogram features from non-invasive arterial spin labeling (ASL)-weighted MRI in differentiating isocitrate dehydrogenase mutant (IDH-mut) and wild type (IDH-wt), and separating lower-grade gliomas (LGGs) from glioblastoma multiforme (GBM).Material and Methods:Methods One hundred thirty-one patients scanned with ASL-weighted and anatomic MRI were retrospectively included. Cerebral blood flow (CBF) maps were calculated, from which 10 histogram features describing the CBF distribution were extracted within the tumor region. Correlation analysis was used to determine correlations between histogram features, and tumor grades and IDH genotypes. Independent t-tests and Fisher\'s exact tests were used to determine the differences in extracted histogram features, age at diagnosis, and gender among different glioma subtypes. Binary logistic regression was used to combine multivariates, and the diagnostic performances were evaluated with receiver operating characteristic curves.Results:Results CBF histogram features were significantly correlated with tumor grades and IDH genotypes, and facilitate the efficacious differentiation of LGGs from GBM, and IDH-mut from IDH-wt gliomas. A model combining the CBF 30th percentile and age at diagnosis resulted in an area under the receiving operating characteristic curve (AUC) of 0.73 in judging LGGs from GBM. Integrating age at the time of diagnosis and CBF 10th percentile allows more comprehensive differentiation of IDH-mut and IDH-wt gliomas, and the combined model achieved an improved AUC of 0.856 (sensitivity, 84.4%; and specificity, 82.9%).Conclusion:Conclusion Histogram features from non-invasive ASL-weighted MRI were significantly correlated with tumor grade and IDH genotypes, and facilitated efficacious differentiation of glioma subtypes. Combining age at the time of diagnosis and perfusion histogram features resulted in a more comprehensive identification of tumor subtypes, which indicated that ASL-weighted MRI can serve as non-invasive tool for the pre-surgical evaluation of gliomas.