IDH1 and central nervous system cancer: In conclusion, training a XGBoost classifier while using multiparametric radiomic features derived from DWI and FLAIR images discriminated IDH1 mutation status with accuracy > 90% and AUC > 0.95, which may provide an approach for noninvasive assessment of IDH1 status in patients with gliomas.