Portal vein preparation for inflow anastomosis is a critical step in liver transplantation. Although portal vein thrombosis is well documented and classified according to Yerdel grading, calcification or sclerosis of the portal vein is rarely reported. Segmental or diffuse calcification of portal vein compromises its structural integrity and may even result in flow obstruction, rendering it unsuitable for reconstruction and necessitating alternative inflow strategies. This case report describes a patient with portal vein tearing around chronic calcification who underwent successful living donor liver transplantation using a cryopreserved iliac vein graft anastomosed to gastric varices.

Objective: Farmers are known to have high prevalence of asthma and chronic obstructive pulmonary disease(COPD). This study aims to investigate the current status of asthma and COPD in domestic and foreign farmers with the ultimate goal of raising awareness of asthma and COPD among farmers and contribute to supporting evidence for the prevention of respiratory diseases in farmers. Methods: The study utilized data from the "Farmer’s Occupational Disease Survey," conducted by the Rural Development Administration, to determine the prevalence of respiratory diseases in domestic farmers.The prevalence of asthma and COPD in overseas farmers was evaluated by researching other foreign studies and articles. Results: The prevalence of asthma and COPD in domestic farmers was less than of foreign farmers’.The prevalence of asthma in domestic farmers was high as upto 8.4% and COPD upto 5.5%. Studies from Europe and America showed prevalence of asthma in farmers high as upto 14.8% and COPD upto 17.1%. Conclusions This study conducted an investigation using the 'Survey on Occupational Diseases and Injuries in Farmers to understand the current status of asthma and COPD in domestic farmers. Due to a lack of relevant domestic research, we examined and compared with the research results on asthma and COPD among overseas farmers. Further research is necessary and preventive measures for respiratory diseases need to be developed.

Gastrointestinal (GI) emergencies in neonates and infants encompass from the beginning to the end of the GI tract. Both congenital and acquired conditions can cause various GI emergencies in neonates and infants. Given the overlapping or nonspecific clinical findings of many different neonatal and infantile GI emergencies and the unique characteristics of this age group, appropriate imaging is key to accurate and timely diagnosis while avoiding unnecessary radiation hazard and medical costs. In this paper, we discuss the radiological findings of essential neonatal and infantile GI emergencies, including esophageal atresia and tracheoesophageal fistula, hypertrophic pyloric stenosis, duodenal atresia, malrotation, midgut volvulus for upper GI emergencies, and jejunoileal atresia, meconium ileus, meconium plug syndrome, meconium peritonitis, Hirschsprung disease, anorectal malformation, necrotizing enterocolitis, and intussusception for lower GI emergencies.

Purpose: This study evaluated the diagnostic performance of contrast-enhanced voiding urosonography (ce-VUS) using a second-generation ultrasound contrast agent for the diagnosis of vesicoureteral reflux (VUR) and intrarenal reflux (IRR), and compared it with that of standard fluoroscopic voiding cystourethrography (VCUG). Methods: Thirty-two consecutive children from April to October 2019 were included in this study. ce-VUS and VCUG were performed simultaneously by two operators with intravesical infusion of a mixture of ultrasound contrast medium, iodinated contrast medium and water. Two pediatric radiologists independently reviewed the ce-VUS and VCUG images and reported the presence and degree of VUR (grades I-V), and the presence and type of IRR. Results: Twenty-seven of 63 urinary systems showed VUR. Interobserver agreement for VUR grading was very good for both examinations (κ=0.87; 95% confidence interval [CI], 0.82 to 0.92 for ce-VUS and κ=0.92; 95% CI, 0.87 to 0.96 for VCUG). The detection rate of VUR showed no significant difference between the two examinations (P=0.370). Four cases of VUR were missed on ce-VUS, while one case of VUR was missed on VCUG. All four false-negative cases on ce-VUS were grade 1 VUR. The two examinations showed very good agreement regarding VUR grading (κ =0.89; 95% CI, 0.81 to 0.96). IRR was more frequently detected with ce-VUS than with VCUG (10 cases with ce-VUS vs. 3 cases with VCUG, P=0.016). Conclusion ce-VUS showed very good agreement with VCUG for detecting grade 2 VUR and above, while grade 1 VUR was sometimes missed with ce-VUS. IRR was more frequently detected with ce-VUS than with VCUG.

Background: As the importance of the esthetic function of teeth increases, the use of esthetic restoration materials and whitening treatment are increasing. The purpose of this study was to investigate the color change of esthetic restoration materials upon using staining and whitening toothpaste. Methods: Light curing (LC) packable composite resin, LC flowable resin, LC glass ionomer (GI), and self-curing GI specimens were colored in coffee or curry for three hours a day for seven days. After that, regular toothpaste, whitening toothpaste containing hydrogen peroxide, and whitening toothpaste containing activated charcoal were applied for three minutes three times a day for two weeks. Luminosity (L), chromaticity a (a), and chromaticity b (b) were measured using a spectrophotometer once a week. Results: In the coffee-colored group, the change in L2 *a2 *b2 (E2 ) with time was significant (p=0.004), there was no difference for different toothpaste types (p=0.646), and there was significant difference (p＜0.001) for different esthetic restorative materials.The change of E2 in the curry-colored group was significant only for different esthetic restorative materials (p＜0.001). In the coffee-colored group, the L, a, and b values of the light-curing GI showed greater change than other materials after staining and one week after whitening, turning dark, red, and yellow. In the curry-colored group, L did not differ for different materials and times, and a and b showed the greatest difference in light-curing GI after staining and one and two weeks after whitening. Conclusion The use of whitening toothpaste for two weeks was not different from the use of general toothpaste in the removal of staining or whitening. Since light-curing GI is the most vulnerable to coloration, it is recommended that coloring by food chromogen should be explained in advance, before using light-curing GI for teeth restoration.

Extrahepatic duct duplication is an extremely rare congenital anomaly. Hilar cholangiocarcinoma with extrahepatic bile duct duplication was reported; however, intraductal papillary neoplasm of the bile duct (IPNB) with extrahepatic bile duct duplication has not been reported to the best of our knowledge. We report a rare case of IPNB with extrahepatic bile duct duplication of a 64-year-old female. The patient underwent extended right hepatectomy, and the results of a subsequence histopathological examination were consistent with an IPNB with extrahepatic bile duct duplication. We report this rare case with radiologic imaging findings and a brief review of the current literature.

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988–0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618– 0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

Src family kinases (SFKs), an important group of non-receptor tyrosine kinases, are suggested to be excessively activated during various types of tissue fibrosis. The present study investigated the effect of KF-1607, an orally active and a newly synthesized Src kinase inhibitor (SKI) with proposed low toxicity, in preventing the progression of renal interstitial fibrosis. Unilateral ureteral obstruction (UUO) surgery was performed in 6-week-old male C57BL/6 mice to induce renal interstitial fibrosis. Either KF-1607 (30 mg/kg, oral gavage) or PP2 (2 mg/kg, intraperitoneal injection), a common experimental SKI, was administered to mice for seven days, started one day prior to surgery. UUO injury-induced SFK expression, including Src, Fyn, and Lyn kinase. SFK inhibition by KF-1607 prevented the progression of tubular injury in UUO mice, as indicated by decreases in albuminuria, urinary KIM-1 excretion, and kidney NGAL protein expression. Renal tubulointerstitial fibrosis was attenuated in response to KF-1607, as shown by decreases in α-SMA, collagen I and IV protein expression, along with reduced Masson’s trichrome and collagen-I staining in kidneys. KF-1607 also inhibited inflammation in the UUO kidney, as exhibited by reductions in F4/80 positive-staining and protein expression of p-NFκB and ICAM. Importantly, the observed effects of KF-1607 were similar to those of PP2. A new pan Src kinase inhibitor, KF-1607, is a potential pharmaceutical agent to prevent the progression of renal interstitial fibrosis.

Extrahepatic duct duplication is an extremely rare congenital anomaly. Hilar cholangiocarcinoma with extrahepatic bile duct duplication was reported; however, intraductal papillary neoplasm of the bile duct (IPNB) with extrahepatic bile duct duplication has not been reported to the best of our knowledge. We report a rare case of IPNB with extrahepatic bile duct duplication of a 64-year-old female. The patient underwent extended right hepatectomy, and the results of a subsequence histopathological examination were consistent with an IPNB with extrahepatic bile duct duplication. We report this rare case with radiologic imaging findings and a brief review of the current literature.

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988–0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618– 0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.