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Radiomics has potential for reflecting the differences in glioma perfusion heterogeneity between arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) imaging. The aim of this study was to compare radiomic features of ASL and DSC imaging-derived parameters (cerebral blood flow, CBF) and assess radiomics-based classification models for low-grade gliomas (LGGs) and high-grade gliomas (HGGs) using their parameters. The ASL-CBF and DSC-relative CBF of 46 glioma patients were normalized (ASL-nCBF and DSC-nrCBF) for data analysis. For each map, 91 radiomic features were extracted from the tumor volume. Seventy-five radiomic features were significantly different ( P  < 0.00055) between ASL-nCBF and DSC-nrCBF. Positive correlations were observed in 75 radiomic features between ASL-nCBF and DSC-nrCBF. Even though ASL imaging underestimated CBF compared with DSC imaging, there were significant correlations ( P  < 0.00055) in the first-order-based mean, median, 90 th  percentile, and maximum. Texture analysis showed that ASL-nCBF and DSC-nrCBF characterized similar perfusion patterns, while ASL-nCBF could evaluate perfusion heterogeneity better. The areas under the curve of the ASL-nCBF and DSC-nrCBF radiomics-based classification models for gliomas were 0.888 and 0.962, respectively. Radiomics in ASL and DSC imaging is useful for characterizing glioma perfusion patterns quantitatively and for classifying LGGs and HGGs.

A radiomics-based comparative study on arterial spin labeling and dynamic susceptibility contrast perfusion-weighted imaging in gliomas