Mapping white matter maturational processes and degrees on neonates by diffusion kurtosis imaging with multiparametric analysis

White matter maturation has been characterized by diffusion tensor (DT) metrics. However, maturational processes and degrees are not fully investigated due to limitations of univariate approaches and limited specificity/sensitivity. Diffusion kurtosis imaging (DKI) provides kurtosis tensor (KT) and white matter tract integrity (WMTI) metrics, besides DT metrics. Therefore, we tried to investigate performances of DKI with the multiparametric analysis in characterizing white matter maturation. Developmental changes in metrics were investigated by using tract‐based spatial statistics and the region of interest analysis on 50 neonates with postmenstrual age (PMA) from 37.43 to 43.57 weeks. Changes in metrics were combined into various patterns to reveal different maturational processes. Mahalanobis distance based on DT metrics (D (M,DT)) and that combing DT and KT metrics (D (M,DT‐KT)) were computed, separately. Performances of D (M,DT‐KT) and D (M,DT) were compared in revealing correlations with PMA and the neurobehavioral score. Compared with DT metrics, WMTI metrics demonstrated additional changing patterns. Furthermore, variations of D (M,DT‐KT) across regions were in agreement with the maturational sequence. Additionally, D (M,DT‐KT) demonstrated stronger negative correlations with PMA and the neurobehavioral score in more regions than D (M,DT). Results suggest that DKI with the multiparametric analysis benefits the understanding of white matter maturational processes and degrees on neonates.