Guo et al. aimed to explore whether multiparametric MRI-based radiomics combined with selected blood inflammatory markers could effectively predict the grade and proliferation in glioma patients and found that the radiomics signature demonstrated good performance in both the training and validation cohorts, with AUCs of 0.92, 0.91, and 0.94 and 0.94, 0.75, and 0.82 for differentiating between low and high-grade gliomas, grade III and grade IV gliomas, and low Ki-67 and high Ki-67, respectively, all better than the clinical model [103]. Here, MKI67 is linked to glioma.