Predictive performance of diffusion spectrum imaging for histological grading and proliferative activity of pediatric intracranial tumors

To compare the diagnostic performance of diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) in grading pediatric intracranial tumors (PITs). Forty-four patients with PITs (mean age 8.39 ± 4.17 years; 18 males) who underwent DWI and diffusion spectrum imaging (DTI, DKI, MAP, and NODDI) were enrolled, and classified into 23 low-grade and 21 high-grade PITs. Diffusion metrics were compared between the low- and high-grade PITs using the Mann-Whitney U test. Receiver operating characteristic (ROC) analysis and Spearman correlations were performed. Sensitivity analysis was performed in 27 pediatric gliomas. The MAP_MSD (mean squared diffusion), MAP_QIV (q-space inverse variance), and DWI_ADC (apparent diffusion coefficient) values were significantly lower, while MAP_NG (non-gaussianity), MAP_NGAx (axial non-gaussianity), MAP_NGRad (radial non-gaussianity), NODDI_ICVF (intracellular volume fraction), and NODDI_ODI (orientation dispersion index) were significantly higher in high-grade PITs than in low-grade PITs ( p < 0.05). All parameters yielded AUCs (areas under the ROC curves) of 0.72–0.82. NODDI_ICVF achieved the highest diagnostic performance for distinguishing PIT grades (AUC = 0.82, p < 0.001), with significant integrated discrimination improvement over DWI (corrected p < 0.05). Sensitivity analysis showed the robustness of MAP parameters in pediatric glioma grading, with favorable efficiency (AUC = 0.75–0.82). Furthermore, MAP, NODDI, and DWI metrics exhibited significant correlations with the Ki-67 index. MAP and NODDI have comparable diagnostic performance to DWI in PIT grading, and may provide new approaches for selecting therapeutic strategies for PITs.