Monitoring Posterior Cerebral Perfusion Changes With Dynamic Susceptibility Contrast-Enhanced Perfusion MRI After Anterior Revascularization Surgery in Pediatric Moyamoya Disease

Objective@#To determine whether dynamic susceptibility contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) can be used to evaluate posterior cerebral circulation in pediatric patients with moyamoya disease (MMD) who underwent anterior revascularization. @*Materials and Methods@#This study retrospectively included 73 patients with MMD who underwent DSC perfusion MRI (age, 12.2 ± 6.1 years) between January 2016 and December 2020, owing to recent-onset clinical symptoms during the follow-up period after completion of anterior revascularization. DSC perfusion images were analyzed using a dedicated software package (NordicICE; Nordic NeuroLab) for the middle cerebral artery (MCA), posterior cerebral artery (PCA), and posterior border zone between the two regions (PCA-MCA). Patients were divided into two groups; the PCA stenosis group included 30 patients with newly confirmed PCA involvement, while the no PCA stenosis group included 43 patients without PCA involvement. The relationship between DSC perfusion parameters and PCA stenosis, as well as the performance of the parameters in discriminating between groups, were analyzed. @*Results@#In the PCA stenosis group, the mean follow-up duration was 5.3 years after anterior revascularization, and visual disturbances were a common symptom. Normalized cerebral blood volume was increased, and both the normalized time-topeak (nTTP) and mean transit time values were significantly delayed in the PCA stenosis group compared with those in the no PCA stenosis group in the PCA and PCA-MCA border zones. TTP PCA (odds ratio [OR] = 6.745; 95% confidence interval [CI] = 2.665–17.074; P < 0.001) and CBVPCA-MCA (OR = 1.567; 95% CI = 1.021–2.406; P = 0.040) were independently associated with PCA stenosis. TTPPCA showed the highest receiver operating characteristic curve area in discriminating for PCA stenosis (0.895; 95% CI = 0.803–0.986). @*Conclusion@#nTTP can be used to effectively diagnose PCA stenosis. Therefore, DSC perfusion MRI may be a valuable tool for monitoring PCA stenosis in patients with MMD.

Development and Evaluation of Deep Learning-Based Automatic Segmentation Model for Skull Zero TE MRI in Children

Purpose@#To develop and evaluate a deep learning technique to automatically segment bone structures in zero echo time (ZTE) for skull magnetic resonance imaging (MRI) in children. @*Materials and Methods@#From January to December 2021, 38 bone ZTE MRIs from infants and children (age range, 1–31 months) were collected for model development.Mask images were generated by manually segmenting the craniofacial bone using a commercial segmentation program. Among them, 35 ZTE series were used to train the three-dimensional (3D)-nnUnet deep learning model and the remaining three series were used for model validation. A temporally different dataset of 19 ZTE bone MRIs obtained in May 2022 from infants and children (age range, 3–168 months) was used to determine the model’s performance. Dice similarity coefficient was calculated for each test case.From 3D volume rendering images, segmentation accuracy, overall image quality, and visibility of cranial sutures were subjectively evaluated on a 5-point scale and compared with ground truth data from manual segmentation. Reasons for segmentation failure were analyzed using axially segmented ZTE images. @*Results@#For the test set, the mean Dice similarity coefficient was 0.985 ± 0.019. The segmentation accuracy was lower than the ground truth without showing a statistically significant difference between the two (3.39 ± 1.11 vs. 3.73 ± 0.77, p = 0.055). The overall image quality and suture visibility showed no significant difference (3.34 ± 0.75 vs.3.42 ± 0.69, p = 0.317; 3.55 ± 0.97 vs. 3.60 ± 0.95, p = 0.157). Common reasons for low segmentation accuracy were well-pneumatized sinuses, metal artifacts, skin at the vertex level, and bones too thin. @*Conclusion@#The deep learning-based automatic segmentation technique of bone ZTE MRIs showed comparable segmentation performance to manual segmentation. Using the deep learning-based segmentation results, acceptable 3D-volume rendering images of craniofacial bones were generated.

The Clinical Study on Aluminum Levels in Patients Undergoing Hemodialysis / 대한신장학회지

PURPOSE: This study was performed to evaluate the aluminum level in hemodialysis patients and to find a correlation between aluminum level and bone specific alkaline phosphatase level. METHODS: Eighty five randomly selected patients with end-stage renal disease, undergoing maintenance hemodialysis treatment over 1 year were studied. Serum aluminum and bone specific alkaline phosphatase concentration were measured. Low dose desferrioxamine test (5 mg/kg) was done. RESULTS: The serum aluminum concentration before and after low dose desferrioxamine test were 4.21+/-2.13 microgram/L and 8.89+/-4.48 microgram/L (p<0.01) respectively. Bone-specific alkaline phosphates and parathyroid hormone concentration were 39.08+/-39.90 mg/dL and 98.27+/-112.92 pg/mL. The aluminum level after desferrioxamine test was correlated with duration of hemodialysis (r=0.238, p=0.03). Aluminum level was not correlated with bone specific alkaline phosphatase level. CONCLUSION: Aluminum level was lower than that of previous studies. Aluminum level was not increased in patients with low bone specific alkaline phosphatase. Thus, it seems that serum aluminum level is not a major problem in hemodialysis patients with lower turnover bone disease. However, confirm diagnosis of aluminum related bone disease in hemodialysis patients needs combined study of bone histology with a large number of cases.