Objective This study aims to evaluate the accuracy of magnetic resonance imaging (MRI) in diagnosing orofacial clefts and proposes specific signs for determining the type of cleft. Methods Pregnant women in whom fetal facial malformations are suspected by ultrasonography (US) underwent 1.5 T MRI. The accuracy of the prenatal US and MRI diagnosis was compared with the postnatal findings. Results A total of 71 fetuses were included in the final analysis, which comprised of 35 cases of isolated cleft lip, six cases of cleft lip and alveolus, 21 cases of cleft lip and palate, four cases of isolated cleft palate, and five normal fetuses. MRI was more sensitive than US (MRI 100%, US 77.5%; Fisher's exact test: MRI vs US P=0.000). The accuracy of MRI for all types was 100%. Specific signs (Inverted T, L/anti‐L, U, and “Notch” signs) were proposed, indicating the normal hard, unilateral cleft, bilateral cleft, and cleft soft palates, respectively, which can facilitate the identification of different types of cleft palates. Conclusion MRI can accurately diagnose the type of cleft based on typical signs, which can serve as a definite diagnostic modality and an effective supplement of US.

The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.

Preterm (PT) birth is a potential factor for abnormal brain development. Although various alterations of cortical structure and functional connectivity in preterm infants have been reported, the underlying microstructural foundation is still undetected thoroughly in PT infants relative to full-term (FT) neonates. To detect the very early cortical microstructural alteration noninvasively with advanced neurite orientation dispersion and density imaging (NODDI) on a whole-brain basis, we used multi-shell diffusion MRI of healthy newborns selected from the Developing Human Connectome Project. 73 PT infants and 69 FT neonates scanned at term-equivalent age were included in this study. By extracting the core voxels of gray matter (GM) using GM-based spatial statistics (GBSS), we found that comparing to FT neonates, infants born preterm showed extensive lower neurite density in both primary and higher-order association cortices (FWE corrected, P < 0.025). Higher orientation dispersion was only found in very preterm subgroup in the orbitofrontal cortex, fronto-insular cortex, entorhinal cortex, a portion of posterior cingular gyrus, and medial parieto-occipital cortex. This study provided new insights into exploring structural MR for functional and behavioral variations in preterm population, and these findings may have marked clinical importance, particularly in the guidance of ameliorating the development of premature brain.

No abstract