Prediction of feeding difficulties in neonates with hypoxic-ischemic encephalopathy using magnetic resonance imaging-derived radiomics features.

BACKGROUND: The mechanisms behind brain and spinal cord injuries in hypoxic-ischemic encephalopathy (HIE) and associated feeding difficulties are unclear, with previous magnetic resonance imaging (MRI) attempts yielding inconclusive results. OBJECTIVE: We aim to evaluate an MRI radiomics model for predicting feeding difficulties in HIE infants. Additionally, we investigate changes in predictive capability after incorporating the duration of mechanical ventilation and the timing of MRI examination. MATERIALS AND METHODS: Retrospective study with 151 HIE infants (January 2013 to December 2021), randomly divided into training and validation sets. Radiomics features extracted from basal ganglia-thalamus and brainstem in T1-weighted and T2-weighted MRI. Established single-modality, single-site, and multimodality/multisite models. Receiver operating characteristic analysis and area under the curve evaluated models. Decision curve analysis assessed changes in predictive capability. RESULTS: The combined radiomics model of the basal ganglia-thalamus and brainstem regions on the T2-weighted imaging demonstrated superior performance (area under the curve: 0.958 and 0.875 for training and validation, respectively). Combining scores with duration of mechanical ventilation and MRI examination time in a calibration plot model improved and stabilized performance, showing high fitting and clinical utility. Decision curve analysis favored the combined calibration plot model. CONCLUSION: The MRI-based radiomics model predicts feeding difficulties in HIE infants, with basal ganglia-thalamus and brainstem as relevant factors. The combined calibration plot model exhibits the highest clinical predictive efficacy.

A cross-sectional study on the correlation of image quality, effective dose, and body composition with thyroid, chest, and abdominal computed tomography scans.

Background: The rapid increase in the use of radiodiagnostic examinations in China, especially computed tomography (CT) scans, has led to these examinations being the largest artificial source of per capita effective dose (ED). This study conducted a retrospective analysis of the correlation between image quality, ED, and body composition in 540 cases that underwent thyroid, chest, or abdominal CT scans. The aim of this analysis was to evaluate the correlation between the parameters of CT scans and body composition in common positions of CT examination (thyroid, chest, and abdomen) and ultimately inform potential measures for reducing radiation exposure. Methods: This study included 540 patients admitted to Fudan University Shanghai Cancer Center from January 2015 to December 2019 who underwent both thyroid or chest or abdominal CT scan and body composition examination. Average CT values and standard deviation (SD) values were collected for the homogeneous areas of the thyroid, chest, or abdomen, and the average CT values and SD values of adjacent subcutaneous fat tissue were measured in the same region of interest (ROI). All data were measured three times, and the average was taken to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for each area. The dose-length product (DLP) was recorded, and the ED was calculated with the following: formula ED = k × DLP. Dual-energy X-ray was used to determine body composition and obtain indicators such as percentage of spinal and thigh muscle. Pearson correlation coefficient was used to analyze the correlations between body composition indicators, height, weight, body mass index (BMI), and ED. Results: The correlation coefficients between the SNR of abdominal CT scan and weight, BMI, and body surface area (BSA) were -0.470 (P=0.001), -0.485 (P=0.001), and -0.437 (P=0.002), representing a moderate correlation strength with statistically significant differences. The correlation coefficients between the ED of chest CT scans and weight, BMI, spinal fat percentage, and BSA were 0.488 (P=0.001), 0.473 (P=0.002), 0.422 (P=0.001), and 0.461 (P=0.003), respectively, indicating a moderate correlation strength with statistical differences. There was a weak statistically significant correlation between the SNR, CNR, and ED of the other scans with each physical and body composition index (P=0.023). Conclusions: There were varying degrees of correlation between CT image quality and ED and physical and body composition indices, which may inform novel solutions for reducing radiation exposure.

The clinical and imaging features of eosinophilic cystitis in children: a case series study.

BACKGROUND: Eosinophilic cystitis (EC) is rare in children and remains poorly understood. Our aim was to analyse the clinical and imaging features of eosinophilic cystitis in children. METHODS: A retrospective review of histologically confirmed eosinophilic cystitis between January 2008 and December 2022 was performed, including patient age, sex, symptoms, laboratory examination, radiology, treatment and outcome. RESULTS: Twelve children (two girls, 10 boys; age range: 3-12 years, mean age: 7.2 years) were included in the study. Urinary irritation symptoms (10/12), haematuria (5/12) and hypogastralgia (3/12) were the most common symptoms. Five patients had a history of allergies, six patients had elevated serum IgE, nine patients had elevated peripheral eosinophils and six patients had positive microscopic haematuria. Radiology revealed diffuse homogeneous or inhomogeneous thickening in seven patients, localised thickening in three patients, and solitary tumour-like lesions in the other two patients. Preservation of the mucosal line and bladder wall layering were observed in eleven patients, and perivesical exudation and small vessel dilatation were observed in ten patients. All four patients with delayed scans showed obvious delayed enhancement. One patient showed low signal intensity on T2-W imaging. All patients received antihistamine, antibiotic and/or corticosteroid therapy and two tumour-like patients underwent transurethral resection. Nine patients achieved complete response and three patients achieved partial response. CONCLUSION: The clinical and imaging manifestations of EC in children have relative characteristics; when urologist and radiologist confronted with similar cases, EC should be considered. The final diagnosis depends on pathological biopsy.

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The male patient was referred to the hospital at 44 days old due to dyspnea after birth and inability to wean off oxygen. His brother died three days after birth due to respiratory failure. The main symptoms observed were respiratory failure, dyspnea, and hypoxemia. A chest CT scan revealed characteristic reduced opacity in both lungs with a "crazy-paving" appearance. The bronchoalveolar lavage fluid (BALF) showed periodic acid-Schiff positive proteinaceous deposits. Genetic testing indicated a compound heterozygous mutation in the ABCA3 gene. The diagnosis for the infant was congenital pulmonary alveolar proteinosis (PAP). Congenital PAP is a significant cause of challenging-to-treat respiratory failure in full-term infants. Therefore, congenital PAP should be considered in infants experiencing persistently difficult-to-treat dyspnea shortly after birth. Early utilization of chest CT scans, BALF pathological examination, and genetic testing may aid in early diagnosis.

Genetic background of idiopathic neurodevelopmental delay patients with significant brain deviation volume.

BACKGROUND: Significant brain volume deviation is an essential phenotype in children with neurodevelopmental delay (NDD), but its genetic basis has not been fully characterized. This study attempted to analyze the genetic factors associated with significant whole-brain deviation volume (WBDV). METHODS: We established a reference curve based on 4222 subjects ranging in age from the first postnatal day to 18 years. We recruited only NDD patients without acquired etiologies or positive genetic results. Cranial magnetic resonance imaging (MRI) and clinical exome sequencing (2742 genes) data were acquired. A genetic burden test was performed, and the results were compared between patients with and without significant WBDV. Literature review analyses and BrainSpan analysis based on the human brain developmental transcriptome were performed to detect the potential role of genetic risk factors in human brain development. RESULTS: We recruited a total of 253 NDD patients. Among them, 26 had significantly decreased WBDV (<-2 standard deviations [SDs]), and 14 had significantly increased WBDV (>+2 SDs). NDD patients with significant WBDV had higher rates of motor development delay (49.8% [106/213] vs . 75.0% [30/40], P  = 0.003) than patients without significant WBDV. Genetic burden analyses found 30 genes with an increased allele frequency of rare variants in patients with significant WBDV. Analyses of the literature further demonstrated that these genes were not randomly identified: burden genes were more related to the brain development than background genes ( P  = 1.656e -9 ). In seven human brain regions related to motor development, we observed burden genes had higher expression before 37-week gestational age than postnatal stages. Functional analyses found that burden genes were enriched in embryonic brain development, with positive regulation of synaptic growth at the neuromuscular junction, positive regulation of deoxyribonucleic acid templated transcription, and response to hormone, and these genes were shown to be expressed in neural progenitors. Based on single cell sequencing analyses, we found TUBB2B gene had elevated expression levels in neural progenitor cells, interneuron, and excitatory neuron and SOX15 had high expression in interneuron and excitatory neuron. CONCLUSION: Idiopathic NDD patients with significant brain volume changes detected by MRI had an increased prevalence of motor development delay, which could be explained by the genetic differences characterized herein.

Cortical and subcortical morphological alteration in Angelman syndrome.

BACKGROUND: Angelman syndrome (AS) is a neurodevelopmental disorder with serious seizures. We aim to explore the brain morphometry of patients with AS and figure out whether the seizure is associated with brain development. METHODS: Seventy-three patients and 26 healthy controls (HC) underwent high-resolution structural brain MRI. Group differences between the HC group and the AS group and also between AS patients with seizure (AS-Se) and age-matched AS patients with non-seizure (AS-NSe) were compared. The voxel-based and surface-based morphometry analyses were used in our study. Gray matter volume, cortical thickness (CTH), and local gyrification index (LGI) were assessed to analyze the cortical and subcortical structure alteration in the AS brain. RESULTS: Firstly, compared with the HC group, children with AS were found to have a significant decrease in gray matter volume in the subcortical nucleus, cortical, and cerebellum. However, the gray matter volume of AS patients in the inferior precuneus was significantly increased. Secondly, patients with AS had significantly increased LGI in the whole brain as compared with HC. Thirdly, the comparison of AS-Se and the AS-NSe groups revealed a significant decrease in caudate volume in the AS-Se group. Lastly, we further selected the caudate and the precuneus as ROIs for volumetric analysis, the AS group showed significantly increased LGI in the precuneus and reduced CTH in the right precuneus. Between the AS-Se and the AS-NSe groups, the AS-Se group exhibited significantly lower density in the caudate, while only the CTH in the left precuneus showed a significant difference. CONCLUSIONS: These results revealed cortical and subcortical morphological alterations in patients with AS, including globally the decreased brain volume in the subcortical nucleus, the increased gray matter volume of precuneus, and the whole-brain increase of LGI and reduction of CTH. The abnormal brain pattern was more serious in patients with seizures, suggesting that the occurrence of seizures may be related to abnormal brain changes.

Disrupted Topological Organization of White Matter Network in Angelman Syndrome.

BACKGROUND: Angelman syndrome (AS) is a genetic disorder that affects neurodevelopment. The investigation of changes in the brain white matter network, which would contribute to a better understanding of the pathogenesis of AS brain, was lacking. PURPOSE: To investigate both local and global alterations of white matter in patients with AS. STUDY TYPE: Prospective. SUBJECTS: A total of 29 AS patients (6.6 ± 1.4 years, 15 [52%] females) and 19 age-matched healthy controls (HC) (7.0 ± 1.5 years, 10 [53%] females). FIELD STRENGTH/SEQUENCE: A 3-T, three-dimensional (3D) T1-weighted imaging by using gradient-echo-based sequence, single shell diffusion tensor imaging by using spin-echo-based echo-planar imaging. ASSESSMENT: Network metrics including global efficiency (Eg ), local efficiency (Eloc ), small world coefficient (Swc), rich-club coefficient (Φ), and nodal degree (ND) were estimated from diffusion MR (dMR) data. Connections among highly connected (hub) regions and less connected (peripheral) regions were also assessed. Correlation between the topological parameters and age for each group was also calculated to assess the development of the brain. STATISTICAL TESTS: Linear regression model, permutation test. P values estimated from the regression model for each brain region were adjusted by false discovery rate (FDR) correction. RESULTS: AS patients showed significantly lower Eg and higher swc compared to HC. Φn significantly increased at higher k-levels in AS patients. In addition, the connections among hub regions and peripheral regions were significantly interrupted in AS patients. DATA CONCLUSION: The AS brain showed diminished connectivity, reflected by reduced network efficiency compared to HC. Compared to densely connected regions, less connected regions were more vulnerable in AS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

The uncovered biases and errors in clinical determination of bone age by using deep learning models.

OBJECTIVES: To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA. METHODS: We established three deep learning models from a Chinese private dataset (CHNm), an American public dataset (USAm), and a joint dataset combining the above two datasets (JOIm). The test data CHNt (n = 1246) were labeled by ten senior pediatric radiologists. The effects of data site differences, interpretation bias, and interobserver variability on BA assessment were evaluated. The differences between the AI models' and radiologists' clinical determinations of BA (normal, advanced, and delayed BA groups by using the Brush data) were evaluated by the chi-square test and Kappa values. The heatmaps of CHNm-CHNt were generated by using Grad-CAM. RESULTS: We obtained an MAD value of 0.42 years on CHNm-CHNt; this result indicated an appropriate accuracy for the whole group but did not indicate an accurate estimation of individual BA because with a kappa value of 0.714, the agreement between AI and human clinical determinations of BA was significantly different. The features of the heatmaps were not fully consistent with the human vision on the X-ray films. Variable performance in BA estimation by different AI models and the disagreement between AI and radiologists' clinical determinations of BA may be caused by data biases, including patients' sex and age, institutions, and radiologists. CONCLUSIONS: The deep learning models outperform external validation in predicting BA on both internal and joint datasets. However, the biases and errors in the models' clinical determinations of child development should be carefully considered. KEY POINTS: • With a kappa value of 0.714, clinical determinations of bone age by using AI did not accord well with clinical determinations by radiologists. • Several biases, including patients' sex and age, institutions, and radiologists, may cause variable performance by AI bone age models and disagreement between AI and radiologists' clinical determinations of bone age. • AI heatmaps of bone age were not fully consistent with human vision on X-ray films.

Imaging features of juvenile xanthogranuloma.

BACKGROUND: Juvenile xanthogranuloma is rare in children and there are limited data on its imaging features. OBJECTIVE: To analyze the computed tomography (CT) and magnetic resonance imaging (MRI) features of juvenile xanthogranuloma in children. MATERIALS AND METHODS: A retrospective review was performed of clinical and radiographic data of histologically confirmed juvenile xanthogranuloma between January 2009 and June 2020. RESULTS: Fourteen children (4 girls, 10 boys; age range: 1 day to 13 years, mean age: 73 months) were included in the study: 4/14 had CT only, 5/14 had MRI only and 5/14 had CT and MRI. Sites of extracutaneous juvenile xanthogranuloma involvement included subcutaneous soft tissue (8/14), liver (2/14), lungs (2/14), kidney (2/14), nose (2/14), pancreas (1/14), central nervous system (1/14) and greater omentum (1/14), mainly manifested as single or multiple nodules or masses in different organs. On CT, the lesions mainly manifested as an iso-hypo density mass with mild or marked enhancement. On MRI, the lesions mainly manifested as slightly hyperintense on T1 and slightly hypointense on T2, with decreased diffusivity and homogeneous enhancement. Juvenile xanthogranuloma was not included in the imaging differential diagnosis in any case. CONCLUSION: Juvenile xanthogranuloma mainly manifests as single or multiple nodules or masses in different organs. Slight hyperintensity on T1 and slight hypointensity on T2 with decreased diffusivity and homogeneous enhancement are relatively characteristic imaging findings of juvenile xanthogranuloma. Combined with its typical skin lesions and imaging features, radiologists should include juvenile xanthogranuloma in the differential diagnosis when confronted with similar cases.

Brain structural alterations in young girls with Rett syndrome: A voxel-based morphometry and tract-based spatial statistics study.

Rett syndrome (RTT) is a neurodevelopmental disorder caused by loss-of-function variants in the MECP2 gene, currently with no cure. Neuroimaging is an important tool for obtaining non-invasive structural and functional information about the in vivo brain. Multiple approaches to magnetic resonance imaging (MRI) scans have been utilized effectively in RTT patients to understand the possible pathological basis. This study combined developmental evaluations with clinical severity, T1-weighted imaging, and diffusion tensor imaging, aiming to explore the structural alterations in cohorts of young girls with RTT, idiopathic autism spectrum disorder (ASD), or typical development. Voxel-based morphometry (VBM) was used to determine the voxel-wised volumetric characteristics of gray matter, while tract-based spatial statistics (SPSS) was used to obtain voxel-wised properties of white matter. Finally, a correlation analysis between the brain structural alterations and the clinical evaluations was performed. In the RTT group, VBM revealed decreased gray matter volume in the insula, frontal cortex, calcarine, and limbic/paralimbic regions; TBSS demonstrated decreased fractional anisotropy (FA) and increased mean diffusivity (MD) mainly in the corpus callosum and other projection and association fibers such as superior longitudinal fasciculus and corona radiata. The social impairment quotient and clinical severity were associated with these morphometric alterations. This monogenic study with an early stage of RTT may provide some valuable guidance for understanding the disease pathogenesis. At the same time, the pediatric-adjusted analytic pipelines for VBM and TBSS were introduced for significant improvement over classical approaches for MRI scans in children.

An in-depth discussion of cholesteatoma, middle ear Inflammation, and langerhans cell histiocytosis of the temporal bone, based on diagnostic results.

Objective: This study aimed to conduct an in-depth investigation of the learning framework used for deriving diagnostic results of temporal bone diseases, including cholesteatoma and Langerhans cell histiocytosis (LCH). In addition, middle ear inflammation (MEI) was diagnosed by CT scanning of the temporal bone in pediatric patients. Design: A total of 119 patients were included in this retrospective study; among them, 40 patients had MEI, 38 patients had histology-proven cholesteatoma, and 41 patients had histology-proven LCH of the temporal bone. Each of the 119 patients was matched with one-third of the disease labels. The study included otologists and radiologists, and the reference criteria were histopathology results (70% of cases for training and 30% of cases for validation). A multilayer perceptron artificial neural network (VGG16_BN) was employed and classified, based on radiometrics. This framework structure was compared and analyzed by clinical experts according to CT images and performance. Results: The deep learning framework results vs. a physician's diagnosis, respectively, in multiclassification tasks, were as follows. Receiver operating characteristic (ROC) (cholesteatoma): (0.98 vs. 0.91), LCH (0.99 vs. 0.98), and MEI (0.99 vs. 0.85). Accuracy (cholesteatoma): (0.99 vs. 0.89), LCH (0.99 vs. 0.97), and MEI (0.99 vs. 0.89). Sensitivity (cholesteatoma): (0.96 vs. 0.97), LCH (0.99 vs. 0.98), and MEI (1 vs. 0.69). Specificity (cholesteatoma): (1 vs. 0.89), LCH (0.99 vs. 0.97), and MEI (0.99 vs. 0.89). Conclusion: This article presents a research and learning framework for the diagnosis of cholesteatoma, MEI, and temporal bone LCH in children, based on CT scans. The research framework performed better than the clinical experts.

Prediction of Hearing Prognosis of Large Vestibular Aqueduct Syndrome Based on the PyTorch Deep Learning Model.

In order to compare magnetic resonance imaging (MRI) findings of patients with large vestibular aqueduct syndrome (LVAS) in the stable hearing loss (HL) group and the fluctuating HL group, this paper provides reference for clinicians' early intervention. From January 2001 to January 2016, patients with hearing impairment diagnosed as LVAS in infancy in the Department of Otorhinolaryngology, Head and Neck Surgery, Children's Hospital of Fudan University were collected and divided into the stable HL group (n = 29) and the fluctuating HL group (n = 30). MRI images at initial diagnosis were collected, and various deep learning neural network training models were established based on PyTorch to classify and predict the two series. Vgg16_bn, vgg19_bn, and ResNet18, convolutional neural networks (CNNs) with fewer layers, had favorable effects for model building, with accs of 0.9, 0.8, and 0.85, respectively. ResNet50, a CNN with multiple layers and an acc of 0.54, had relatively poor effects. The GoogLeNet-trained model performed best, with an acc of 0.98. We conclude that deep learning-based radiomics can assist doctors in accurately predicting LVAS patients to classify them into either fluctuating or stable HL types and adopt differentiated treatment methods.

Common and Distinct Disruptions of Cortical Surface Morphology Between Autism Spectrum Disorder Children With and Without SHANK3 Deficiency.

SH3 and Multiple Ankyrin Repeat Domains 3 (SHANK3)-caused autism spectrum disorder (ASD) may present a unique opportunity to clarify the heterogeneous neuropathological mechanisms of ASD. However, the specificity and commonality of disrupted large-scale brain organization in SHANK3-deficient children remain largely unknown. The present study combined genetic tests, neurobehavioral evaluations, and magnetic resonance imaging, aiming to explore the disruptions of both local and networked cortical structural organization in ASD children with and without SHANK3 deficiency. Multiple surface morphological parameters such as cortical thickness (CT) and sulcus depth were estimated, and the graph theory was adopted to characterize the topological properties of structural covariance networks (SCNs). Finally, a correlation analysis between the alterations in brain morphological features and the neurobehavioral evaluations was performed. Compared with typically developed children, increased CT and reduced nodal degree were found in both ASD children with and without SHANK3 defects mainly in the lateral temporal cortex, prefrontal cortex (PFC), temporo-parietal junction (TPJ), superior temporal gyrus (STG), and limbic/paralimbic regions. Besides commonality, our findings showed some distinct abnormalities in ASD children with SHANK3 defects compared to those without. Locally, more changes in the STG and orbitofrontal cortex were exhibited in ASD children with SHANK3 defects, while more changes in the TPJ and inferior parietal lobe (IPL) in those without SHANK3 defects were observed. For the SCNs, a trend toward regular network topology was observed in ASD children with SHANK3 defects, but not in those without. In addition, ASD children with SHANK3 defects showed more alterations of nodal degrees in the anterior and posterior cingulate cortices and right insular, while there were more disruptions in the sensorimotor areas and the left insular and dorsomedial PFC in ASD without SHANK3 defects. Our findings indicate dissociable disruptions of local and networked brain morphological features in ASD children with and without SHANK3 deficiency. Moreover, this monogenic study may provide a valuable path for parsing the heterogeneity of brain disturbances in ASD.

Amplitude of low-frequency fluctuation may be an early predictor of delayed motor development due to neonatal hyperbilirubinemia: a fMRI study.

BACKGROUND: Acute bilirubin encephalopathy or kernicterus is the worst consequence of brain damage caused by the elevation of total unbound serum bilirubin (TSB) in neonates. The present study aimed to visualize the characteristic brain regions of neonates with hyperbilirubinemia (HB) using functional magnetic resonance imaging (fMRI) and to measure the amplitude of low-frequency fluctuation (ALFF) values. METHODS: This was a prospective cohort study, which included newborns with HB who were hospitalized at the Children's Hospital of Fudan University. The control group included neonates admitted with neonatal simple wet lung or pneumonia without neurological disease or brain injury. Newborns were divided into a severe hyperbilirubinemia group (SHB), moderate HB group, and control group based on TSB levels. The newborns completed routine MRI combined with fMRI scans and brainstem auditory evoked potentials (BAEPs) during their hospitalization. RESULTS: A total of 251 newborns were included in this study. There were 45 patients in the SHB group, 65 in the HB group, and 141 in the control group. The average ALFF value in the basal ganglia region in the SHB group was the highest, which was greater than that in the HB and control groups (P<0.001). The ALFF increased with an increase in TSB concentration. Based on the results of the Bayley Scales of infant development assessment, we further found that the most significant difference in ALFF remained in the basal ganglia region between newborns with motor development scores above 70 (including 70) and below 70. Correlation analysis revealed a strong negative correlation between motor development scores and ALFF (r=-0.691, P<0.001). When ALFF alone was used to predict motor development, the sensitivity was 89%. When ALFF was combined with TSB and BEAP results, the area under the ROC curve was the largest (AUC =0.85). The sensitivity and specificity of the model were 67.86% and 90.77%, respectively. CONCLUSIONS: The ALFF value may be able to serve as an early imaging biomarker and has a greater sensitivity than TSB or BAEP results in predicting long-term motor development (18 m) in HB.

A retrospective clinical analysis of pediatric paragonimiasis in a Chinese children's hospital from 2011 to 2019.

Diagnosis of pediatric paragonimiasis is difficult because of its non-specific clinical manifestations. We retrospectively reviewed the records of pediatric paragonimiasis in Children's Hospital of Fudan University from January 2011 to May 2019. The confirmed diagnosis of paragonimiasis was based on positive anti-parasite serological tests from the local Center for Disease Control (CDC). A total of 11 patients (mean age: 7.7 ± 3.1, male-female ratio: 7:4) diagnosed as paragonimiasis were included. 81.8% were from endemic areas such as Sichuan and Yunnan, and 36% had a clear history of raw crab or crayfish consumption. The characteristic clinical features of pediatric paragonimiasis were eosinophilia (100%), pleural effusion (81.8%), hepatomegaly (54.5%), ascites (54.5%), and subcutaneous nodules (45.5%). Misdiagnosed with other diseases including tuberculosis (18.2%), pneumonia (9.1%), intracranial space-occupying lesions (9.1%) and brain abcess (9.1%) led to rehospitalization and prolonged hospitalization. For treatment, a 3-day course of 150 mg/kg praziquantel (PZQ) didn't show ideal treatment effectivity and 63.6% needed more than one course of PZQ, while triclabendazole in a total dose of 10 mg/kg had a better efficacy to stubborn manifestations. This study indicated that pediatric paragonimiasis was often misdiagnosed, and the treatment with a 3-day course of 150 mg/kg PZQ had a high rate of failure.

Altered striatum centered brain structures in SHANK3 deficient Chinese children with genotype and phenotype profiling.

SHANK3 deficiency represents one of the most replicated monogenic risk factors for autism spectrum disorder (ASD) and SHANK3 caused ASD presents a unique opportunity to understand the underlying neuropathological mechanisms of ASD. In this study, genetic tests, comprehensive clinical and neurobehavioral evaluations, as well as multimodal structural MRI using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were conducted in SHANK3 group (N = 14 with SHANK3 defects), ASD controls (N = 26 with idiopathic ASD without SHANK3 defects) and typically developing (TD) controls (N = 32). Phenotypically, we reported several new features in Chinese SHANK3 deficient children including anteverted nares, sensory stimulation seeking, dental abnormalities and hematological problems. In SHANK3 group, VBM revealed decreased grey matter volumes mainly in dorsal striatum, amygdala, hippocampus and parahippocampal gyrus; TBSS demonstrated decreased fractional anisotropy in multiple tracts involving projection, association and commissural fibers, including middle cerebral peduncle, corpus callosum, superior longitudinal fasciculus, corona radiata, external and internal capsule, and posterior thalamic radiation, etc. We report that the disrupted striatum centered brain structures are associated with SHANK3 deficient children. Study of subjects with monogenic cause offer specific insights into the neuroimaging studies of ASD. The discovery may support a path for future functional connectivity studies to allow for more in-depth understandings of the abnormal neural circuits and the underlying neuropathological mechanisms for ASD.

Risk Factors for Hydrocephalus in Neonatal Purulent Meningitis: A Single-Center Retrospective Analysis.

OBJECTIVE: Hydrocephalus is a potentially lethal complication of neonatal purulent meningitis. Early detection of hydrocephalus helps to determine optimal treatment, improve prognosis, and reduce financial burden. We aimed to analyze the risk factors for hydrocephalus in neonates with purulent meningitis and discuss the characteristics of the disease. METHODS: The records of neonatal purulent meningitis admitted to the Children Hospital of Fudan University from January 2013 to September 2019 were retrospectively included in the study cohort. The data of clinical, laboratory, and cranial magnetic resonance images (MRIs) were collected and analyzed (except discharge data) by univariate analysis, and P values <.05 were further analyzed by multivariate logistic regression. RESULTS: A total of 197 children who met the inclusion criteria were enrolled in the study cohort. Overall, 39.6% (78/197) of the patients had positive pathogen cultures, and 60.4% (119/197) of patients had clinical diagnosis of meningitis with negative pathogen cultures. Among 197 children, 67 of them experienced hydrocephalus, and the factors that were significantly associated with hydrocephalus in multivariate analysis were female sex, cerebrospinal fluid glucose <2 mmol/L, periventricular leukomalacia, punctate white matter lesions, and pyogenic intraventricular empyema. Children with hydrocephalus had a lower cure rate of meningitis (31.3% vs 75.4%), and poor discharge outcomes. In addition, they had longer length of hospital stay and higher hospital cost. CONCLUSIONS: Female sex, cerebrospinal fluid glucose <2 mmol/L, periventricular leukomalacia, punctate white matter lesions, and pyogenic intraventricular empyema were identified as risk factors for hydrocephalus in neonatal purulent meningitis. Children with hydrocephalus had poor discharge outcomes and increased financial burden on their families.

DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution.

Thin-section magnetic resonance imaging (MRI) can provide higher resolution anatomical structures and more precise clinical information than thick-section images. However, thin-section MRI is not always available due to the imaging cost issue. In multicenter retrospective studies, a large number of data are often in thick-section manner with different section thickness. The lack of thin-section data and the difference in section thickness bring considerable difficulties in the study based on the image big data. In this article, we introduce DeepVolume, a two-step deep learning architecture to address the challenge of accurate thin-section MR image reconstruction. The first stage is the brain structure-aware network, in which the thick-section MR images in axial and sagittal planes are fused by a multitask 3-D U-net with prior knowledge of brain volume segmentation, which encourages the reconstruction result to have correct brain structure. The second stage is the spatial connection-aware network, in which the preliminary reconstruction results are adjusted slice-by-slice by a recurrent convolutional network embedding convolutional long short-term memory (LSTM) block, which enhances the precision of the reconstruction by utilizing the previously unassessed sagittal information. We used 305 paired brain MRI samples with thickness of 1.0 mm and 6.5 mm in this article. Extensive experiments illustrate that DeepVolume can produce the state-of-the-art reconstruction results by embedding more anatomical knowledge. Furthermore, considering DeepVolume as an intermediate step, the practical and clinical value of our method is validated by applying the brain volume estimation and voxel-based morphometry. The results show that DeepVolume can provide much more reliable brain volume estimation in the normalized space based on the thick-section MR images compared with the traditional solutions.

Differential diagnosis of pancreatoblastoma (PB) and solid pseudopapillary neoplasms (SPNs) in children by CT and MR imaging.

OBJECTIVES: To determine whether features on computed tomographic and/or magnetic resonance imaging can differentiate pancreatoblastoma (PB) from solid pseudopapillary neoplasms (SPNs) of the pancreas in children. METHODS: Clinical and imaging data for 20 cases of SPNs and 14 cases of PB confirmed by surgery or biopsy were retrospectively analysed. The size, border, calcification, haemorrhage, solid/cystic component proportion, intratumoural vessels, tumour capsulation, pancreatic duct dilatation, peripancreatic vessel invasion, distant metastasis status and apparent diffusion coefficient (ADC) values of the two groups were examined, and key diagnostic features were identified. Statistical analysis was performed using the chi-square test and Student's t test. Sensitivity and specificity values were calculated when a single criterion was used. RESULTS: Age ≤ 5 years, elevated serum α-fetoprotein (AFP), larger size, ill-defined border, calcification, absence of haemorrhage, intratumoural vessel, peripancreatic vessel invasion and distant metastasis differentiated PB from SPN (p < 0.05). ADC values of SPN were higher than those of PB (p = 0.001). There were no significant differences regarding tumour capsule (p = 0.435), pancreatic duct dilatation (p = 1.000) or cystic degeneration area over 50% of the tumour volume (p = 1.000) between the two groups. CONCLUSIONS: The following features are helpful for differentiating PB from SPN: age ≤ 5 years, elevated serum AFP, larger size, ill-defined border, calcification, haemorrhage absence, intratumoural vessel, peripancreatic vessel invasion, distant metastasis and lower ADC value. KEY POINTS: • CT and MRI are helpful to differentiate pancreatoblastoma (PB) from solid pseudopapillary neoplasms (SPNs) of the pancreas in children. • The following features are helpful to differentiate PB from SPN: age ≤ 5 years, elevated serum AFP, larger size, ill-defined border, calcification, absence of haemorrhage, intratumoural vessel, peripancreatic vessel invasion, distant metastasis and lower ADC value.