Shear wave elastography and dispersion imaging for hepatic veno-occlusive disease prediction after pediatric hematopoietic stem cell transplantation: a feasibility study.

BACKGROUND: Non-invasive imaging modalities are warranted for diagnosing and monitoring veno-occlusive disease because early diagnosis and treatment improve the prognosis. OBJECTIVE: To evaluate the usefulness of liver shear wave elastography (SWE) and shear wave dispersion (SWD) imaging in diagnosing and monitoring veno-occlusive disease in pediatric patients. MATERIALS AND METHODS: We conducted a prospective cohort study at a single tertiary hospital from March 2021 to April 2022. The study protocol included four ultrasound (US) sessions: a baseline US and three follow-up US after hematopoietic stem cell transplantation. Clinical criteria, including the European Society for Blood and Marrow Transplantation criteria, were used to diagnose veno-occlusive disease. We compared clinical factors and US parameters between the veno-occlusive disease and non-veno-occlusive disease groups. The diagnostic performance of US parameters for veno-occlusive disease was assessed by plotting receiver operating characteristic (ROC) curves. We describe temporal changes in US parameters before and after veno-occlusive disease diagnosis. RESULTS: Among the 38 participants (mean age 10.7 years), eight developed veno-occlusive disease occurring 17.0 ± 5.2 days after hematopoietic stem cell transplantation. Liver stiffness, as measured by SWE (15.0 ± 6.2 kPa vs. 5.8 ± 1.8 kPa; P<0.001), and viscosity, as assessed with SWD (17.7 ± 3.1 m/s/kHz vs. 14.3 ± 2.8 m/s/kHz; P=0.015), were significantly higher in the veno-occlusive disease group compared to the non-veno-occlusive disease group at the time of diagnosis. Liver stiffness demonstrated the highest area under the ROC (AUROC) curves at 0.960, with an optimal predictive value of >6.5 kPa, resulting in sensitivity and specificity of 100% and 83.3%, respectively. Viscosity demonstrated an AUROC of 0.783, with an optimal cutoff value of 13.9 m/s/kHz for predicting veno-occlusive disease, with a sensitivity of 100% and specificity of 53.3%, respectively. Liver stiffness increased with disease severity and decreased during post-treatment follow-up. CONCLUSION: SWE may be a promising technique for early diagnosis and severity prediction of veno-occlusive disease. Furthermore, liver viscosity assessed by SWD may serve as an additional marker of veno-occlusive disease.

Feasibility of a deep learning artificial intelligence model for the diagnosis of pediatric ileocolic intussusception with grayscale ultrasonography.

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 modelgenerated 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.

Primary renal lymphoma presenting as renal failure: A case report and review of literature from 1989.

BACKGROUND: Primary renal lymphoma (PRL) is extremely rare with an incidence of 0.7% among extranodal lymphomas. Occult renal lymphoma, which mimics medical renal disease and bilateral renal involvement, presents a diagnostic challenge to nephrologists and radiologists as the clinical and radiological findings are mostly non-specific or inconclusive. Acute kidney injury (AKI) is not an uncommon finding in renal infiltration due to malignant lymphoma. However, only 14% of cases are detected before death, and the low diagnostic rate may be due to the non-specific clinical manifestations of renal involvement, with only 0.5% of these cases presenting with AKI. Moreover, PRL is difficult to diagnose based on clinical, biochemical, and radiologic features, especially, in the case of bilateral diffuse involvement. CASE SUMMARY: Herein, we report a 74-year-old woman with primary diffuse large B-cell lymphoma who presented with AKI diagnosed by ultrasound-guided needle biopsy. We also report the clinicopathologic findings of 121 PRL cases reported since 1989, by conducting a literature review of published cases. CONCLUSION: A timely renal biopsy provides the most expedient means of establishing the diagnosis. Thus, early identification of the disease by the clinician facilitates early diagnosis toward effective treatment.

Ultra-low-dose computed tomography with deep learning reconstruction for craniosynostosis at radiation doses comparable to skull radiographs: a pilot study.

BACKGROUND: Craniofacial computed tomography (CT) is the diagnostic investigation of choice for craniosynostosis, but high radiation dose remains a concern. OBJECTIVE: To evaluate the image quality and diagnostic performance of an ultra-low-dose craniofacial CT protocol with deep learning reconstruction for diagnosis of craniosynostosis. MATERIALS AND METHODS: All children who underwent initial craniofacial CT for suspected craniosynostosis between September 2021 and September 2022 were included in the study. The ultra-low-dose craniofacial CT protocol using 70 kVp, model-based iterative reconstruction and deep learning reconstruction techniques was compared with a routine-dose craniofacial CT protocol. Quantitative analysis of the signal-to-noise ratio and noise was performed. The 3-dimensional (D) volume-rendered images were independently evaluated by two radiologists with regard to surface coarseness, step-off artifacts and overall image quality on a 5-point scale. Sutural patency was assessed for each of six sutures. Radiation dose was compared between the two protocols. RESULTS: Among 29 patients (15 routine-dose CT and 14 ultra-low-dose CT), 23 patients had craniosynostosis. The 3-D volume-rendered images of ultra-low-dose CT without deep learning showed decreased image quality compared to routine-dose CT. The 3-D volume-rendered images of ultra-low-dose CT with deep learning reconstruction showed higher noise level, higher surface coarseness but decreased step-off artifacts, comparable signal-to-noise ratio and overall similar image quality compared to the routine-dose CT images. Diagnostic performance for detecting craniosynostosis at the suture level showed no significant difference between ultra-low-dose CT without deep learning reconstruction, ultra-low-dose CT with deep learning reconstruction and routine-dose CT. The estimated effective radiation dose for the ultra-low-dose CT was 0.05 mSv (range, 0.03-0.06 mSv), a 95% reduction in dose over the routine-dose CT at 1.15 mSv (range, 0.54-1.74 mSv). This radiation dose is comparable to 4-view skull radiography (0.05-0.1 mSv) and lower than previously reported effective dose for craniosynostosis protocols (0.08-3.36 mSv). CONCLUSION: In this pilot study, an ultra-low-dose CT protocol using radiation doses at a level similar to skull radiographs showed preserved diagnostic performance for craniosynostosis, but decreased image quality compared to the routine-dose CT protocol. However, by combining the ultra-low-dose CT protocol with deep learning reconstruction, image quality was improved to a level comparable to the routine-dose CT protocol, without sacrificing diagnostic performance for craniosynostosis.

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-to-peak (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. TTPPCA (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.

Contrast-enhanced ultrasound for the diagnosis of acute pyelonephritis in pediatric patients with urinary tract infection: A feasibility study.

PURPOSE: This study aimed to assess the feasibility of contrast-enhanced ultrasound (CEUS) for the diagnosis of acute pyelonephritis (APN) in pediatric patients with febrile urinary tract infection (UTI). MATERIALS AND METHODS: Between March 2019 and January 2021, study participants with suspected UTI were assessed for APN using ultrasound. Parenchymal echogenicity changes, renal pelvis dilatation, and the presence of a focal suspected lesion were assessed using conventional grayscale ultrasound. The presence and location of a decreased perfusion area were evaluated using color Doppler ultrasound (CDUS) and CEUS. Agreement between each ultrasound examination and a 99mTc‒dimercaptosuccinic acid (DMSA) scan was assessed using the κ value, and the most visible period of the lesion was evaluated using CEUS. RESULTS: This study enrolled 21 participants (median age, 8.0 months; range, 2.0-61.0 months) with isolated urinary tract pathogens. Five increased parenchymal echotextures (11.9%) and 14 renal pelvic dilatations (33.3%) were confirmed, but no focal lesions were detected on the grayscale images. CDUS and CEUS showed decreased local perfusion suggestive of APN in two and five kidneys, respectively. DMSA scan showed substantial agreement with CEUS findings (κ = 0.80, P = 0.010), but other grayscale and CDUS findings did not agree with DMSA scan results (P > 0.05). All lesions were best observed in the late parenchymal phase on CEUS. CONCLUSION: CEUS can reveal renal perfusion defects in pediatric patients with suspected APN without radiation exposure or sedation; therefore, CEUS may be a feasible and valuable diagnostic technique.

Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.

OBJECTIVE: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. MATERIALS AND METHODS: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. RESULTS: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). CONCLUSION: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

Usefulness of two-dimensional shear wave elastography in diagnosing hepatic veno-occlusive disease in pediatric patients undergoing hematopoietic stem cell transplantation.

PURPOSE: This study aimed to evaluate the usefulness of two-dimensional shear wave elastography (2D-SWE) in diagnosing hepatic veno-occlusive disease (VOD) in pediatric patients. METHODS: This study retrospectively included pediatric patients who underwent hematopoietic stem cell transplantation (HSCT) between November 2019 and January 2021. All 34 patients (8.7±5.0 years) were examined using 2D-SWE for an initial diagnosis. A subgroup analysis was performed using the data from follow-up examinations of patients diagnosed with VOD. The characteristics of the initial VOD diagnosis were compared with the longitudinal changes observed in VOD patients who underwent multiple ultrasound examinations. RESULTS: In total, 19 patients were diagnosed with VOD at 17.6±9.4 days after HSCT. All VOD patients showed hepatomegaly, ascites, and gallbladder wall thickening. Liver stiffness was higher in VOD patients than in non-VOD patients (12.4±1.1 vs. 6.3±0.8 kPa, P<0.001). Liver stiffness values above 7.2 kPa showed 84.2% sensitivity and 93.3% specificity in distinguishing VOD from non-VOD (area under the curve, 0.925; 95% confidence interval, 0.780 to 0.987; P<0.001). A subgroup analysis of 11 patients showed a linear decrease in liver stiffness values after VOD diagnosis with treatment (first, second, and third follow-ups; 13.5±1.7, 11.3±1.4, and 9.5±0.8 kPa, respectively), but without statistical significance in the pairwise analysis. CONCLUSION: Liver stiffness measured using 2D-SWE increased in pediatric patients who develop VOD after HSCT. Therefore, liver stiffness can be a predictive and quantitative parameter for diagnosing VOD.

Identification and characterization of gut-associated lactic acid bacteria isolated from the bean bug, Riptortus pedestris (Hemiptera: Alydidae).

Lactic acid bacteria (LAB) are beneficial bacteria for humans and animals. However, the characteristics and functions of LAB in insects remain unclear. Here, we isolated LAB from the gut of Riptortus pedestris, a pest that is a significant problem in soybean cultivation in Korea, and identified two Lactococcus lactis and one Enterococcus faecalis using matrix-associated laser desorption/ionization-time of flight and 16S rRNA analyses. All three LAB strains survived at pH 8, and L. lactis B103 and E. faecalis B105 survived at pH 9 for 24 h. In addition, these strains survived well in simulated gastric juice of humans containing pepsin and exhibited high resistance to bile salts. Two strains of L. lactis and one of E. faecalis maintained constant density (> 104 colony-forming units [CFU]/mL) at pH 2.5, but viability at pH 2.2 was strain-dependent. The three LAB were reinoculated into second-instar nymphs of R. pedestris and colonized well, reaching a constant density (> 105 CFU/gut) in the adult insect gut. Interestingly, feeding of these LAB increased the survival rate of insects compared to the negative control, with the largest increase seen for L. lactis B103. However, the LAB did not increase the weight or length of adult insects. These results indicate that insect-derived LAB possess the traits required for survival under gastrointestinal conditions and have beneficial effects on insect hosts. The LAB infection frequency of the wild bean bug populations was 89% (n = 18) in Gyeongsangnam-do, South Korea. These LAB can be utilized as a novel probiotic in the cultivation of beneficial insects. This study provides fundamental information about the symbiosis between insects and LAB, and a novel concept for pest control.

Expression of Three Clones of PD-L1 in Lung Cancer: A Single-center Experience.

BACKGROUND/AIM: Programmed cell death ligand 1 (PD-L1) is an immune checkpoint protein involved in immune evasion of malignant tumors. Confirmation of PD-L1 expression in non-small cell lung cancer (NSCLC) is necessary for the determination of immunotherapy using immune checkpoint inhibitors (ICIs). PDL-1 expression is currently analyzed by immunohistochemistry and is the only available biomarker that can guide the treatment of NSCLC using ICIs. The present study was conducted to compare the expression of three different commercial clones of PD-L1 in order for immunohistochemistry (IHC) for these clones to become more reliable for surgical pathologists. MATERIALS AND METHODS: This study examined the expression of PD-L1 in 76 cases of resected lung cancer using IHC. Three clones were examined: SP263, SP142, and 22C3PharmDx, which are commercially approved for quantifying PD-L1 expression in lung cancer. RESULTS: Of the 76 patients whose samples were evaluated for PD-L1 using the IHC 22C3pharmDx assay, 19 (25.0%) had a tumor proportion score (TPS) of ≥50% and 41 (53.9%) had a PD-L1 TPS of ≥1%. Furthermore, using the SP263, 48.7% had a TPS of ≥1% and 18.4% of >50%. The SP142 assay was used to evaluate tumor cells (TCs) and immune cells (ICs). Twenty (26.3%) cases were positive for TCs and 25 (32.9%) were reactive for ICs. CONCLUSION: These three commercial PD-L1 clones are comparable for detecting primary targets for anti-tumor immunotherapies. Careful evaluation by a pathologist is necessary to minimize misinterpretation errors.

Factors influencing outcomes of esophageal balloon dilatation for anastomosis site stenosis after esophageal atresia surgery.

BACKGROUND: Esophageal balloon dilatation is an effective treatment for anastomotic strictures, but the factors affecting the outcome of dilatation remain unclear. OBJECTIVE: To investigate the predictive factors of esophageal balloon dilatation outcome in children with anastomotic stricture after esophageal atresia repair. MATERIALS AND METHODS: We retrospectively reviewed children with esophageal atresia who underwent esophageal balloon dilatation for postoperative strictures between August 2007 and February 2021. We investigated each child's age, weight and height; type of esophageal atresia surgery; shape, length and level of stricture; esophageal balloon dilatation balloon size; application of mitomycin; number of inflation sessions; and number of esophageal balloon dilatation sessions. The outcome of each esophageal balloon dilatation session was determined as improvement in stricture diameter between pre- and post-esophageal balloon dilatation esophagography. We used uni- and multivariate analyses with generalized estimating equations to evaluate outcome predictors. RESULTS: Overall, 69 children (mean age, 2.3 years; 45 boys) underwent 227 esophageal balloon dilatations. In the univariate analysis, the positive effect of esophageal balloon dilatation decreased with increased age, weight, height, balloon size and number of esophageal balloon dilatation sessions. Additionally, the positive effect was decreased in cervical-level strictures and with the application of mitomycin during esophageal balloon dilatation. In the multivariate analysis, independent prognostic factors of the positive esophageal balloon dilatation effect were age (incidence rate ratio [IRR]: -0.01; 95% confidence interval [CI]: -0.01, -0.002), shape of stricture (IRR: -0.54; 95% CI: -0.91, -0.18) and number of esophageal balloon dilatation sessions (IRR, -0.10; 95% CI: -0.14, -0.18). CONCLUSION: Repeated esophageal balloon dilatation, older age and eccentric stricture shape are associated with poor response to esophageal balloon dilatation in children with anastomotic strictures after esophageal atresia repair.

Deep learning reconstruction in pediatric brain MRI: comparison of image quality with conventional T2-weighted MRI.

INTRODUCTION: Deep learning-based MRI reconstruction has recently been introduced to improve image quality. This study aimed to evaluate the performance of deep learning reconstruction in pediatric brain MRI. METHODS: A total of 107 consecutive children who underwent 3.0 T brain MRI were included in this study. T2-weighted brain MRI was reconstructed using the three different reconstruction modes: deep learning reconstruction, conventional reconstruction with an intensity filter, and original T2 image without a filter. Two pediatric radiologists independently evaluated the following image quality parameters of three reconstructed images on a 5-point scale: overall image quality, image noisiness, sharpness of gray-white matter differentiation, truncation artifact, motion artifact, cerebrospinal fluid and vascular pulsation artifacts, and lesion conspicuity. The subjective image quality parameters were compared among the three reconstruction modes. Quantitative analysis of the signal uniformity using the coefficient of variation was performed for each reconstruction. RESULTS: The overall image quality, noisiness, and gray-white matter sharpness were significantly better with deep learning reconstruction than with conventional or original reconstruction (all P < 0.001). Deep learning reconstruction had significantly fewer truncation artifacts than the other two reconstructions (all P < 0.001). Motion and pulsation artifacts showed no significant differences among the three reconstruction modes. For 36 lesions in 107 patients, lesion conspicuity was better with deep learning reconstruction than original reconstruction. Deep learning reconstruction showed lower signal variation compared to conventional and original reconstructions. CONCLUSION: Deep learning reconstruction can reduce noise and truncation artifacts and improve lesion conspicuity and overall image quality in pediatric T2-weighted brain MRI.

Indian Almond (Terminalia catappa Linn.) Leaf Extract Extends Lifespan by Improving Lipid Metabolism and Antioxidant Activity Dependent on AMPK Signaling Pathway in Caenorhabditis elegans under High-Glucose-Diet Conditions.

This study aimed to evaluate the antioxidant and antiaging effects of Indian almond (Terminalia catappa Linn.) leaf extract (TCE) on high-glucose (GLU)-induced obese Caenorhabditis elegans. Since TCE contains high contents of flavonoids and phenolics, strong radical scavenging activity was confirmed in vitro. The stress-resistance effect of TCE was confirmed under thermal and oxidative stress conditions at nontoxic tested concentrations (6.25, 12.5, and 25 µg/mL). GLU at 2% caused lipid and reactive oxygen species (ROS) accumulation in C. elegans, and TCE inhibited lipid and ROS accumulation under both normal and 2% GLU conditions in a concentration-dependent manner. In addition, TCE proved to be effective in prolonging the lifespan of C. elegans under normal and 2% GLU conditions. The ROS reduction effect of TCE was abolished in mutants deficient in daf-16/FOXO and skn-1/Nrf-2. In addition, the lifespan-extending effect of TCE in these two mutants disappeared. The lifespan-extending effect was abolished even in atgl-1/ATGL-deficiency mutants. The TCE effect was reduced in aak-1/AMPK-deficient mutants and completely abolished under 2% GLU conditions. Therefore, the effect of prolonging lifespan by inhibiting lipid and ROS accumulation under the high GLU conditions of TCE is considered to be the result of atgl-1, daf-16, and skn-1 being downregulated by aak-1. These results suggest that the physiological potential of TCE contributes to antiaging under metabolic disorders.

Case mistaken for leukemia after mRNA COVID-19 vaccine administration: A case report.

BACKGROUND: Following the global outbreak of coronavirus disease 2019 (COVID-19), unlike other vaccines, COVID-19 vaccines were developed and commercialized in a relatively short period of time. The large-scale administration of this vaccine in a short time-period led to various unexpected side effects, including severe cytopenia and thrombosis with thrombocytopenia syndrome. Despite many reports on adverse reactions, vaccination was necessary to prevent the spread of COVID-19; thus, it is essential to understand and discuss various cases of adverse reactions after vaccination. CASE SUMMARY: A 77-year-old woman was administered the second dose of Pfizer mRNA COVID-19 vaccine. After vaccination she experienced fever, myalgia, and weakness. Antibiotics were subsequently administered for several days, but there was no improvement in the symptoms. The patient showed severe thrombocytopenia and leukocytosis. Thoracic and abdominopelvic computed tomography showed no infection related findings, but splenomegaly and cirrhotic liver features were observed. A large number of immature cells were observed in the peripheral blood smear; thus, bone marrow examination was performed for acute leukemia. However, there were no abnormalities. The patient recovered after administration of hepatotoxins and transfusion treatment for cytopenia and was diagnosed with an adverse reaction to COVID-19 vaccination. CONCLUSION: Adverse reactions of vaccination could be mistaken for hematologic malignancies including leukemia. We report a patient with leukocytosis following COVID-19 vaccination.

[Jaundice in Young Children]. / 소아 황달의 영상 평가.

Jaundice in children have various etiologies. Among them, physiological jaundice is a very common disease observed in more than half of full-term neonates. When jaundice persists or develops after 2 weeks of age, the total/direct bilirubin is measured in consideration of the possibility of cholestasis. In case of cholestasis, imaging studies differentiate biliary atresia and other disorders of the extrahepatic bile ducts. In this review, we briefly presented the major differential diseases of cholestasis in children and introduced diagnostic imaging techniques, including normal findings.

Non-secretory multiple myeloma expressed as multiple extramedullary plasmacytoma with an endobronchial lesion mimicking metastatic cancer: A case report.

BACKGROUND: Non-secretory multiple myeloma (MM) is a rare condition that accounts for only 3% of MM cases and is defined by normal serum and urine immunofixation and a normal serum free light chain ratio. Non-secretory MM with multiple extramedullary plasmacytomas derived from endobronchial lesions is extremely rare and can be misdiagnosed as metastasis of solid cancer. CASE SUMMARY: A 36-year-old man presented with progressive facial swelling and nasal congestion with cough. Various imaging studies revealed an endobronchial mass in the left bronchus and a large left maxillary mass with multiple destructive bone metastatic lesions. He initially presented with lung cancer and multiple metastases. However, pathologic reports showed multiple extramedullary plasmacytomas in the left maxilla and the left bronchus. There was no change in the serum and urine monoclonal protein levels, and no abnormalities were observed in laboratory examinations, including hemoglobin, calcium, and creatinine levels. The bone marrow was hypercellular, with 13.49% plasma cells. The patient was diagnosed with non-secretory MM expressed as multiple extramedullary plasmacytomas with endobronchial lesions in a rare location. Radiation therapy for symptomatic lesions with high-dose dexamethasone was started, and the size of the left maxillary sinus lesion dramatically decreased. In the future, chemotherapy will be administered to control lesions in other areas. CONCLUSION: We present a rare case of non-secretory MM with multiple extramedullary plasmacytoma with an endobronchial lesion.

Development and evaluation of deep-learning measurement of leg length discrepancy: bilateral iliac crest height difference measurement.

BACKGROUND: Leg length discrepancy (LLD) is a common problem that can cause long-term musculoskeletal problems. However, measuring LLD on radiography is time-consuming and labor intensive, despite being a simple task. OBJECTIVE: To develop and evaluate a deep-learning algorithm for measurement of LLD on radiographs. MATERIALS AND METHODS: In this Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study, radiographs were obtained to develop a deep-learning algorithm. The algorithm developed with two U-Net models measures LLD using the difference between the bilateral iliac crest heights. For performance evaluation of the algorithm, 300 different radiographs were collected and LLD was measured by two radiologists, the algorithm alone and the model-assisting method. Statistical analysis was performed to compare the measurement differences with the measurement results of an experienced radiologist considered as the ground truth. The time spent on each measurement was then compared. RESULTS: Of the 300 cases, the deep-learning model successfully delineated both iliac crests in 284. All human measurements, the deep-learning model and the model-assisting method, showed a significant correlation with ground truth measurements, while Pearson correlation coefficients and interclass correlations (ICCs) decreased in the order listed. (Pearson correlation coefficients ranged from 0.880 to 0.996 and ICCs ranged from 0.914 to 0.997.) The mean absolute errors of the human measurement, deep-learning-assisting model and deep-learning-alone model were 0.7 ± 0.6 mm, 1.1 ± 1.1 mm and 2.3 ± 5.2 mm, respectively. The reading time was 7 h and 12 min on average for human reading, while the deep-learning measurement took 7 min and 26 s. The radiologist took 74 min to complete measurements in the deep-learning mode. CONCLUSION: A deep-learning U-Net model measuring the iliac crest height difference was possible on teleroentgenograms in children. LLD measurements assisted by the deep-learning algorithm saved time and labor while producing comparable results with human measurements.

Adjuvant antimicrobial activity and resensitization efficacy of geraniol in combination with antibiotics on Acinetobacter baumannii clinical isolates.

Adjuvant use of geraniol, a plant essential oil component, is known to increase the efficacy of antibiotics by acting as a potent inhibitor of efflux mechanisms. In this study, we assessed the effect of a geraniol-antibiotic combination in 21 Acinetobacter baumannii clinical isolates consisting of high efflux (HE) and low efflux (LE) activity groups. We determined the MIC for geraniol and the four antibiotics and evaluated the adjuvant antimicrobial activity and resensitization efficacy of adjuvant geraniol. Geraniol-antibiotic combinations significantly reduced the MIC of all four antibiotics (P < 0.0001), and the fold change in MIC decreased by 4 to >256-fold for tigecycline, >16 to >4,096-fold for ceftazidime, 1 to >4,096-fold for cefepime, and >2 to >4096-fold for ciprofloxacin. Importantly, geraniol showed adjuvant antimicrobial activity and resensitization efficacy when used in combination with antibiotics in 21 A. baumannii clinical isolates. However, there was no statistically significant difference between the HE and LE groups. Low concentrations (0.125% and 0.0625%) of geraniol showed no cytotoxic or hemolytic activity. Our study shows that geraniol, acting as an antibiotic adjuvant, is a good candidate for in vivo studies of combination therapy for the treatment of MDR/XDR A. baumannii infections.

Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network.

OBJECTIVES: To develop an automatic segmentation algorithm using a deep neural network with transfer learning applicable to whole-body PET-CT images in children. METHODS: For model development, we utilized transfer learning with a pre-trained model based on adult patients. We used CT images of 31 pediatric patients under 19 years of age (mean age, 9.6 years) who underwent PET-CT from institution #1 for transfer learning. Two radiologists manually labeled the skin, bone, muscle, abdominal visceral fat, subcutaneous fat, internal organs, and central nervous system in each CT slice and used these as references. For external validation, we collected 14 pediatric PET/CT scans from institution #2 (mean age, 9.1 years). The Dice similarity coefficients (DSCs), sensitivities, and precision were compared between the algorithms before and after transfer learning. In addition, we evaluated segmentation performance according to sex, age (≤ 8 vs. > 8 years), and body mass index (BMI, ≤ 20 vs. > 20 kg/m2). RESULTS: The algorithm after transfer learning showed better performance than the algorithm before transfer learning for all body compositions (p < 0.001). The average DSC, sensitivity, and precision of each algorithm before and after transfer learning were 98.23% and 99.28%, 98.16% and 99.28%, and 98.29% and 99.28%, respectively. The segmentation performance of the algorithm was generally not affected by age, sex, or BMI, except for precision in the body muscle compartment. CONCLUSION: The developed model with transfer learning enabled accurate and fully automated segmentation of multiple tissues on whole-body CT scans in children. KEY POINTS: • We utilized transfer learning with a pre-trained segmentation algorithm for adult to develop an algorithm for automated segmentation of pediatric whole-body CT. • This algorithm showed excellent performance and was not affected by sex, age, or body mass index, except for precision in body muscle.

Accuracy of ASTA MicroIDSys, a new matrix-assisted laser desorption/ionization time-of-flight mass spectrometry system, for the identification of Korean reference and clinical bacterial and yeast strains.

This study compared the accuracy of a new MALDI-TOF mass spectrometry system, ASTA MicroIDSys system, with that of MALDI Biotyper system for the identification of reference and clinical bacterial and yeast strains. The identification accuracy of the 2 systems was compared using a total of 406 strains comprising 142 aerobic and 180 anaerobic bacterial strains and 84 yeast strains. The genus and species identification rates were 98.0% and 89.4% using MicroIDSys and 96.1% and 89.4% using Biotyper, respectively. The species identification rates of MicroIDSys and Biotyper for aerobic bacteria were 93.0% and 97.2%, respectively, and those for anaerobic bacteria were 85.6% and 81.7%, respectively. The accuracy of yeast identification at the species level was 91.7% using MicroIDSys and 92.9% using Biotyper. These findings indicate that MicroIDSys could be useful for the accurate identification of bacteria and yeast in clinical microbiology laboratories.