Purpose: Cystic duct cancers (CDCs) have been classified as extrahepatic bile duct cancers or gallbladder cancers (GBCs); however, it is unclear whether their clinical behavior is similar to that of distal extrahepatic bile duct cancers (DBDCs) or GBCs. Materials and Methods: T category of the CDCs was classified using current T category scheme of the GBCs and DBDCs, and clinicopathological factors were compared among 38 CDCs, 345 GBCs, and 349 DBDCs. We modified Nakata’s classifications (type 1, confined within cystic duct [CD]; combined types 2-4, extension beyond CD) and compared them. Results: No significant overall survival (OS) difference was observed between the patients with CDC, GBC, and DBDC. The T category of GBC staging was more accurate at distinguishing OS in patients with CDC than the DBDC staging. Patients with T3 CDC and GBC showed a significant OS difference when using the T category for GBC staging, while those with T1-T2 CDC and GBC showed no significant difference. In contrast, the T category of DBDC staging did not show any significant OS difference between patients with T1-T2 CDC and DBDC or T3 CDC and DBDC. Patients with type 1 CDC had significantly better OS than those with combined types. Conclusion Unlike GBCs and DBDCs, CDCs exhibit distinct clinicopathological characteristics. The OS is better when the CDC confines within the CD, compared to when it extends beyond it. Therefore, we propose a new T category scheme (T1, confined to CD; T2, invaded beyond CD) for better classifying CDCs.

Purpose: Cystic duct cancers (CDCs) have been classified as extrahepatic bile duct cancers or gallbladder cancers (GBCs); however, it is unclear whether their clinical behavior is similar to that of distal extrahepatic bile duct cancers (DBDCs) or GBCs. Materials and Methods: T category of the CDCs was classified using current T category scheme of the GBCs and DBDCs, and clinicopathological factors were compared among 38 CDCs, 345 GBCs, and 349 DBDCs. We modified Nakata’s classifications (type 1, confined within cystic duct [CD]; combined types 2-4, extension beyond CD) and compared them. Results: No significant overall survival (OS) difference was observed between the patients with CDC, GBC, and DBDC. The T category of GBC staging was more accurate at distinguishing OS in patients with CDC than the DBDC staging. Patients with T3 CDC and GBC showed a significant OS difference when using the T category for GBC staging, while those with T1-T2 CDC and GBC showed no significant difference. In contrast, the T category of DBDC staging did not show any significant OS difference between patients with T1-T2 CDC and DBDC or T3 CDC and DBDC. Patients with type 1 CDC had significantly better OS than those with combined types. Conclusion Unlike GBCs and DBDCs, CDCs exhibit distinct clinicopathological characteristics. The OS is better when the CDC confines within the CD, compared to when it extends beyond it. Therefore, we propose a new T category scheme (T1, confined to CD; T2, invaded beyond CD) for better classifying CDCs.

Purpose: Cystic duct cancers (CDCs) have been classified as extrahepatic bile duct cancers or gallbladder cancers (GBCs); however, it is unclear whether their clinical behavior is similar to that of distal extrahepatic bile duct cancers (DBDCs) or GBCs. Materials and Methods: T category of the CDCs was classified using current T category scheme of the GBCs and DBDCs, and clinicopathological factors were compared among 38 CDCs, 345 GBCs, and 349 DBDCs. We modified Nakata’s classifications (type 1, confined within cystic duct [CD]; combined types 2-4, extension beyond CD) and compared them. Results: No significant overall survival (OS) difference was observed between the patients with CDC, GBC, and DBDC. The T category of GBC staging was more accurate at distinguishing OS in patients with CDC than the DBDC staging. Patients with T3 CDC and GBC showed a significant OS difference when using the T category for GBC staging, while those with T1-T2 CDC and GBC showed no significant difference. In contrast, the T category of DBDC staging did not show any significant OS difference between patients with T1-T2 CDC and DBDC or T3 CDC and DBDC. Patients with type 1 CDC had significantly better OS than those with combined types. Conclusion Unlike GBCs and DBDCs, CDCs exhibit distinct clinicopathological characteristics. The OS is better when the CDC confines within the CD, compared to when it extends beyond it. Therefore, we propose a new T category scheme (T1, confined to CD; T2, invaded beyond CD) for better classifying CDCs.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: To compare the Doppler sonographic findings of the left renal vein (LRV) of children diagnosed with nutcracker syndrome with and without orthostatic proteinuria. Methods: Fifty and 53 consecutive children with and without orthostatic proteinuria, respectively, underwent renal Doppler ultrasonography examinations. The peak velocity (PV) was measured at the hilar portion of the LRV and between the aorta and superior mesenteric artery. Renal Doppler ultrasonography findings and clinical data including urine protein-to-creatinine ratio (UPCR) were compared according to the presence or absence of orthostatic proteinuria. Results: Between the two groups, no significant differences were observed in terms of age or sex. The PV ratio between the aortomesenteric and hilar portions was 7.79±2.65 and 6.32±3.01 in children with and without orthostatic proteinuria, respectively (P=0.009). No significant differences were observed between the two groups in terms of the UPCR in the first morning urine sample. However, the UPCR in the afternoon urine sample was significantly higher in children with orthostatic proteinuria than in those without orthostatic proteinuria (0.49±0.46 vs. 0.11±0.04 mg/mg, P<0.001). Furthermore, the PV ratio between the aortomesenteric and hilar portions revealed a positive correlation with the ratio of UPCR of the afternoon and that of first morning urine samples (R=0.21, P=0.034). Conclusions This study suggests that there can be a significant correlation of the PV ratio between the aortomesenteric and hilar portion of the LRV with orthostatic proteinuria in pediatric patients with nutcracker syndrome.

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.