Leptomeningeal enhancement of myelin oligodendrocyte glycoprotein antibody-associated encephalitis: uncovering novel markers on contrast-enhanced fluid-attenuated inversion recovery images.

Background: Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a newly defined autoimmune inflammatory demyelinating central nervous system (CNS) disease characterized by antibodies against MOG. Leptomeningeal enhancement (LME) on contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) images has been reported in patients with other diseases and interpreted as a biomarker of inflammation. This study retrospectively analyzed the prevalence and distribution of LME on CE-FLAIR images in children with MOG antibody-associated encephalitis (MOG-E). The corresponding magnetic resonance imaging (MRI) features and clinical manifestations are also presented. Methods: The brain MRI images (native and CE-FLAIR) and clinical manifestations of 78 children with MOG-E between January 2018 and December 2021 were analyzed. Secondary analyses evaluated the relationship between LME, clinical manifestations, and other MRI measures. Results: Forty-four children were included, and the median age at the first onset was 70.5 months. The prodromal symptoms were fever, headache, emesis, and blurred vision, which could be progressively accompanied by convulsions, decreased level of consciousness, and dyskinesia. MOG-E showed multiple and asymmetric lesions in the brain by MRI, with varying sizes and blurred edges. These lesions were hyperintense on the T2-weighted and FLAIR images and slightly hypointense or hypointense on the T1-weighted images. The most common sites involved were juxtacortical white matter (81.8%) and cortical gray matter (59.1%). Periventricular/juxtaventricular white matter lesions (18.2%) were relatively rare. On CE-FLAIR images, 24 (54.5%) children showed LME located on the cerebral surface. LME was an early feature of MOG-E (P = 0.002), and cases without LME were more likely to involve the brainstem (P = 0.041). Conclusion: LME on CE-FLAIR images may be a novel early marker among patients with MOG-E. The inclusion of CE-FLAIR images in MRI protocols for children with suspected MOG-E at an early stage may be useful for the diagnosis of this disease.

Clinical findings, diagnosis and therapy of patent ductus venosus in children: a case series.

Background: Patent ductus venosus (PDV) is a rare form of congenital portosystemic shunt. Because of the diversity of clinical symptoms and insufficient knowledge of this condition, clinicians often fail to perform targeted examinations, resulting in missed diagnoses and misdiagnoses. This study summarized the clinical and radiological findings, as well as surgical methods, of PDV with the aim of improving early diagnosis and guiding treatment. Methods: Clinical, laboratory, and radiologic data of patients with PDV were analyzed retrospectively. In all, 9 patients with PDV were included in the study (7 male, 2 female; median age 1.6 years, age range 16 days to 16.5 years). Results: Data for all 9 patients with PDV were reviewed. The most common initial clinical presentations were jaundice and respiratory symptoms. Laboratory data revealed hypoxemia in 5 patients, hyperammonemia in 2, hyperbilirubinemia in 7, abnormal coagulation function in 6, abnormal myocardial enzymes in 4, hepatic dysfunction in 8, and renal dysfunction in 3. The direct imaging sign of PDV was a vascular structure connecting the left branch of the portal vein (LPV) to the inferior vena cava. Secondary imaging findings observed in all 9 patients were dilated right heart, pulmonary artery, and LPV, and an atrophic right branch of the portal vein. The main portal vein was dilated in 8 patients and shrunk in 1. Moreover, 8 patients had enlarged livers, and 3 presented with hypoperfusion in the right lobe of the liver. The spleen was enlarged in 8 patients but shrunk in 1. Renal imaging was abnormal in 2 patients. Hepatic encephalopathy was found in 4 patients; 7 patients had PDV combined with other malformations, with congenital heart disease and vascular abnormalities being the most common; 3 patients successfully underwent surgical ligation of PDV. Conclusions: PDV can lead to multisystem damage. Secondary radiological signs of PDV play an important role in early diagnosis and preoperative evaluation. Complications and coexisting malformations were common and should not be missed during preoperative evaluation. Early surgical closure for PDV is recommended.

Individual Brain Morphological Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation for Autism Spectrum Disorder Identification.

Background: Structural magnetic resonance imaging (sMRI) reveals abnormalities in patients with autism spectrum syndrome (ASD). Previous connectome studies of ASD have failed to identify the individual neuroanatomical details in preschool-age individuals. This paper aims to establish an individual morphological connectome method to characterize the connectivity patterns and topological alterations of the individual-level brain connectome and their diagnostic value in patients with ASD. Methods: Brain sMRI data from 24 patients with ASD and 17 normal controls (NCs) were collected; participants in both groups were aged 24-47 months. By using the Jensen-Shannon Divergence Similarity Estimation (JSSE) method, all participants's morphological brain network were ascertained. Student's t-tests were used to extract the most significant features in morphological connection values, global graph measurement, and node graph measurement. Results: The results of global metrics' analysis showed no statistical significance in the difference between two groups. Brain regions with meaningful properties for consensus connections and nodal metric features are mostly distributed in are predominantly distributed in the basal ganglia, thalamus, and cortical regions spanning the frontal, temporal, and parietal lobes. Consensus connectivity results showed an increase in most of the consensus connections in the frontal, parietal, and thalamic regions of patients with ASD, while there was a decrease in consensus connectivity in the occipital, prefrontal lobe, temporal lobe, and pale regions. The model that combined morphological connectivity, global metrics, and node metric features had optimal performance in identifying patients with ASD, with an accuracy rate of 94.59%. Conclusion: The individual brain network indicator based on the JSSE method is an effective indicator for identifying individual-level brain network abnormalities in patients with ASD. The proposed classification method can contribute to the early clinical diagnosis of ASD.