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Purpose Radiographic examinations are frequently performed for diagnostic and therapeutic purposes in neonatal intensive care units (NICUs). However, concerns are emerging regarding the safety of radiation exposure, especially in vulnerable preterm infants in periods of rapid cellular division. This quality improvement (QI) project aimed to reduce radiation hazards in level-IV NICU. Methods We established an "X-ray prescription protocol" and educated the physicians to ensure that only essential radiographs were obtained. Additionally, we discouraged full-body infantograms and emphasized the prescription of targeted radiographs, such as chest or abdominal radiographs. Furthermore, to reduce the dose-area product (DAP, Gy·cm2) values, which act as a surrogate for radiation exposure, we provided training to radiologic technologists on meticulous collimation for each radiography session. We aimed to achieve a 30% reduction in the average monthly cumulative DAP per patient, which was calculated by dividing the total monthly DAP from radiographs in the NICU by the monthly average of patient admissions. Retrospective baseline data were collected 8 months pre-intervention and prospectively for 4 months post-interventions. Results The average monthly X-ray count per patient was 28.3 in the pre-intervention period (October 2022 to May 2023), which decreased to 25.4 in the post-intervention period (June 2023 to September 2023), reflecting a 10.2% reduction (p=0.109). The average monthly infantogram count per patient showed an 18.0% reduction (25.9% to 21.2%, p=0.016), and the proportion of infantograms in the total X-ray counts decreased from 91.5% to 83.3% (p=0.017). The DAP value per X-ray decreased by 42.6%, from an average of 0.25 to 0.14 (p=0.011). The primary outcome, the average monthly cumulative DAP value per patient, showed a substantial reduction of 48.6%, dropping from 7.00 to 3.60 (p=0.004). The baseline characteristics and short-term morbidities of the patients did not differ significantly between the pre- and post-intervention period. Conclusion Our QI approach, which included discouraging excessive prescriptions of infantograms and promoting optimal collimation, significantly reduced the average monthly radiation exposure in the NICU, benefiting both patients and healthcare workers.

Abstract Retained medullary cord (RMC) is a recently defined term denoting closed spinal dysraphism arising from the failure of regression in secondary neurulation. Despite the acknowledgment of this condition, there needs to be more literature elucidating the radiologic manifestations of RMC. This study aimed to describe the MR imaging findings of RMC. A retrospective analysis was conducted on spinal MRI scans of pediatric patients with surgically confirmed RMC, from January 2014 to August 2023. The investigation focused on evaluating the following image characteristics: level and morphology of the cord-like structure (C-LS), the signal intensity in the far distal C-LS, nerve root-like structures originating from the C-LS, intradural fatty lesions, and arachnoid cysts. This study included 38 patients (19 girls, mean age 7.3 months) who showed a low-lying cord in all cases. The morphology of C-LS was either smooth tapered (50%) or hourglass with fusiform cystic dilatation (50%). The C-LS exhibited aberrant T2 hypointense signal compared to the juxta-proximal level. T2 hypointense signal vestigial nerves emanating from the C-LS and intradural fatty masses were observed (89.5%). Sacral arachnoid cysts in extradural location were identified in eight patients. The characteristic MR features of RMC revealed an extremely low-lying distal C-LS with smooth tapering or hourglass-shaped cystic dilatation of the caudal part, accompanied by an intradural fatty stalk and the aberrant signal vestigial nerve. This study suggests those radiologic findings can be RMC instead of the previously called terminal syrinx with low-lying conus.

Abstract Background Chronic enteropathy associated with SLCO2A1 gene (CEAS) is a unique type of inflammatory bowel disease. CEAS is monogenic disease and is thought to develop from childhood, but studies on pediatric CEAS are scarce. We analyzed characteristics of pediatric CEAS. Methods Eleven patients diagnosed with CEAS at Seoul National University Children’s Hospital were identified and analyzed. Clinical data of patients were collected. Sanger sequencing of SLCO2A1 was performed on all patients. Results Patients were diagnosed at a median age of 16.0 years (IQR 11.0 ~ 20.0), and the median age at symptoms onset was only 4.0 years (IQR 2.5 ~ 6.0). Growth delay was observed at the time of diagnosis. Patients showed multiple ulcers or strictures in the small intestine, while the esophagus and colon were unaffected in any patients. Almost half of the patients underwent small intestine resection. The major laboratory features of pediatric CEAS include iron deficiency anemia (IDA), hypoalbuminemia, and near-normal levels of C-reactive protein (CRP). Two novel mutations of SLCO2A1 were identified. The most prevalent symptoms were abdominal pain and pale face. None of the immunomodulatory drugs showed a significant effect on CEAS. Conclusions Pediatric CEAS typically develop from very young age, suggesting it as one type of monogenic very early onset inflammatory bowel disease. CEAS can cause growth delay in children but there is no effective treatment currently. We recommend screening for SLCO2A1 mutations to pediatric patients with chronic IDA from a young age and small intestine ulcers without elevation of CRP levels.

Developmental dysplasia of the hip is a condition characterized by hip joint instability due to acetabular dysplasia in infancy, necessitating precise ultrasound examination. Legg- Calvé-Perthes disease is caused by a temporary disruption in blood flow to the femoral head during childhood, progressing through avascular, fragmentation, re-ossification, and residual stages. Slipped capital femoral epiphysis is a condition where the femoral head shifts medially along the epiphyseal line during adolescence due to stress, such as weight-bearing. Differentiating between transient hip synovitis and septic arthritis may require joint fluid aspiration. Osteomyelitis can be associated with soft tissue edema and osteolysis. When multiple lesions are present, it is essential to distinguish between Langerhans cell histiocytosis and metastatic neuroblastoma. This review will introduce imaging techniques and typical findings for these conditions.

Purpose This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the model-generated confidence score, as determined from the ITS, was verified using the ETS. Results The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

This study presents a new density filter for a pipe-shaped structure and its application to fluid topology optimization. A simple and straight pipe-shaped structure for fluid is preferred for many engineering purposes rather than the perplex manifold structure provided by the topology optimization method. To determine an optimal pipe structure for fluid, we develop a new density filter and apply it to fluid topology optimization. Hence, the original spatially varying design variables of the fluid topology optimization are modified based on the pipe density filter. Subsequently, the filter design variables, including a uniform pipe wall thickness and adjusted cross-section, are used for artificial pseudo-rigid bodies in fluid topology optimization. An additional constraint is imposed to maintain a nearly uniform pipe thickness. Several numerical examples are solved to demonstrate the validity of the present pipe density filter for fluid topology optimization problems minimizing the energy dissipation of the fluid and controlling the particles suspended in the fluid. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to predict high-risk neuroblastoma among neuroblastic tumors using radiomics features extracted from MRI. Materials and Methods: Pediatric patients (age≤18 years) diagnosed with neuroblastic tumors who had pre-treatment MR images available were enrolled from institution A from January 2010 to November 2019 (training set) and institution B from January 2016 to January 2022 (test set). Segmentation was performed with regions of interest manually drawn along tumor margins on the slice with the widest tumor area by two radiologists. First-order and texture features were extracted and intraclass correlation coefficients (ICCs) were calculated. Multivariate logistic regression (MLR) and random forest (RF) models from 10-fold cross-validation were built using these features. The trained MLR and RF models were tested in an external test set. Results: Thirty-two patients (M:F=23:9, 26.0±26.7 months) were in the training set and 14 patients (M:F=10:4, 33.4±20.4 months) were in the test set with radiomics features (n=930) being extracted. For 10 of the most relevant features selected, intra- and interobserver variability was moderate to excellent (ICCs 0.633–0.911, 0.695–0.985, respectively). The area under the receiver operating characteristic curve (AUC) was 0.94 (sensitivity 67%, specificity 91%, and accuracy 84%) for the MLR model and the average AUC was 0.83 (sensitivity 44%, specificity 87%, and accuracy 75%) for the RF model from 10-fold cross-validation. In the test set, AUCs of the MLR and RF models were 0.94 and 0.91, respectively. Conclusion: An MRI-based radiomics model can help predict high-risk neuroblastoma among neuroblastic tumors. [ABSTRACT FROM AUTHOR]