Preoperative imaging findings to predict 2-year native liver survival after the Kasai procedure in patients with biliary atresia.

OBJECTIVES: To investigate the feasibility of using preoperative imaging indices to predict 2-year native liver survival after the Kasai procedure in patients with biliary atresia (BA). MATERIALS AND METHODS: The retrospective review included 190 BA patients who underwent the Kasai procedure between 2000 and 2020, with preoperative US and/or MRI, excluding cases with less than 2-year follow-up period. Multivariable logistic regression analysis was performed to identify imaging indices to predict 2-year native liver survival. Kasai failure was defined as the need for liver transplantation or death within 2 years of the Kasai procedure. RESULTS: Of the 90 patients included, all had preoperative US, and 61 also had MRI. Kasai failure occurred in 52% (47/90). Preoperative US identified gallbladder length (OR 0.40, 95% CI 0.17-0.95, p = 0.039; cutoff 1.6 cm, AUC 67.66) and biliary cysts (OR 24.64, 95% CI 1.97-308.08, p = 0.013) as significant Kasai failure predictors, with a combined accuracy of 73% (60/82). For patients having both preoperative US and MRI, significant predictors were hepatic artery diameter (OR 6.75, 95% CI 1.31-34.88, p = 0.023; cutoff 2 mm, AUC 73.83) and biliary cysts (OR 23.89, 95% CI 1.43-398.82, p = 0.027) on US, and gallbladder length (OR 0.25, 95% CI 0.08-0.76, p = 0.014; cutoff 1.2 cm, AUC 74.72) and spleen size (OR 2.53, 95% CI 1.02-6.29, p = 0.045; cutoff 6.9 cm, AUC 73.72) on MRI, with a combined accuracy of 85% (52/61). CONCLUSION: Preoperative US and/or MRI enhance the 2-year native liver survival prediction in BA patients after the Kasai procedure. CLINICAL RELEVANCE STATEMENT: BA patients with hepatic artery diameter > 2 mm (US), gallbladder length < 1.6 cm (US) or < 1.2 cm (MRI), spleen size > 6.9 cm (MRI), and absence of biliary cysts (US/MRI) have a decreased likelihood of 2-year native liver survival. KEY POINTS: • Preoperative US and/or MRI can predict the probability of achieving 2-year native liver survival following the Kasai procedure. • Combining US and MRI improved the accuracy to 85% for predicting 2-year native liver survival in BA patients. • The hepatic artery diameter > 2 mm (US), gallbladder length < 1.6 cm (US) or < 1.2 cm (MRI), spleen size > 6.9 cm (MRI), and no biliary cysts (US/MRI) are significant predictors of Kasai failure in patients with biliary atresia.

Superb Microvascular Imaging in Pediatric Focal Nodular Hyperplasia.

OBJECTIVE: To investigate superb microvascular imaging (SMI), a novel Doppler ultrasound technique that can visualize low-velocity microvascular flow, for assessing pediatric focal nodular hyperplasia (FNH). PATIENTS AND METHODS: Nine FNH lesions in 6 patients were enrolled. On SMI and color Doppler imaging (CDI), intralesional vascularity was assessed visually and categorized as typical spoke-wheel pattern (central vessel radiating from the center to the periphery), multifocal spoke-wheel pattern, and nonspecific pattern. We compared the vascular features of the lesions between SMI and CDI and evaluated vascular patterns according to lesion size. RESULTS: In terms of vascularity pattern, the typical spoke-wheel pattern of FNH was noted more frequently on SMI (67%) than on CDI (11%; P < 0.05). In addition, a multifocal spoke-wheel pattern was noted in all remaining lesions (33%) on SMI. On the contrary, a nonspecific vascular pattern was detected in the majority (78%) of CDI. Regarding the lesion size and vascularity on SMI, the typical spoke-wheel pattern was seen more frequently in the small FNH group than in the large FNH group. The intralesional vascular signal was detected more frequently on SMI (100%) than on CDI (89%). CONCLUSION: SMI is feasible in evaluating FNH in children and has a greater ability to demonstrate the spoke-wheel pattern than CDI.

Validation of the Pandemic Grief Risk Factors and Its Relationship With Work-Related Stress and Grief Reaction Among Healthcare Workers Who Witnessed Patient Deaths.

BACKGROUND: The Pandemic Grief Risk Factors (PGRFs) was developed as a self-report tool to compile a comprehensive list of unique risk factors related to grief when experiencing a coronavirus disease 2019 (COVID-19) loss. We explored the reliability and validity of the PGRF among healthcare workers who witnessed their patients' deaths during the COVID-19 pandemic. Further, we examined whether the general severity of PGRF may have been associated with work-related stress and pandemic grief reactions. METHODS: An online survey was conducted among tertiary hospital healthcare workers (doctors and nursing professionals) who had witnessed the deaths of patients they cared for. Pandemic Grief Scale for healthcare workers, the Stress and Anxiety to Viral Epidemics-3 items, the Patient Health Questionnaire-9, and the Generalized Anxiety Disorder-7 responses were collected. RESULTS: In total, 267 responses were analyzed. The single-factor structure of the Korean version of the PGRF showed a good fit for the model. The scale demonstrated good internal consistency and convergent validity with other depression and anxiety rating scales. The mediation analysis revealed that work-related stress directly influenced pandemic grief reactions positively, and depression, anxiety, and general severity of grief risk factors partially mediated the association positively. CONCLUSION: Among healthcare workers who witnessed the deaths of their patients due to COVID-19, the Korean version of the PGRF was valid and reliable for measuring the overall severity of PGRF. The PGRF can be used to identify individuals at risk for dysfunctional grief.

Adapt-cMolGPT: A Conditional Generative Pre-Trained Transformer with Adapter-Based Fine-Tuning for Target-Specific Molecular Generation.

Small-molecule drug design aims to generate compounds that target specific proteins, playing a crucial role in the early stages of drug discovery. Recently, research has emerged that utilizes the GPT model, which has achieved significant success in various fields to generate molecular compounds. However, due to the persistent challenge of small datasets in the pharmaceutical field, there has been some degradation in the performance of generating target-specific compounds. To address this issue, we propose an enhanced target-specific drug generation model, Adapt-cMolGPT, which modifies molecular representation and optimizes the fine-tuning process. In particular, we introduce a new fine-tuning method that incorporates an adapter module into a pre-trained base model and alternates weight updates by sections. We evaluated the proposed model through multiple experiments and demonstrated performance improvements compared to previous models. In the experimental results, Adapt-cMolGPT generated a greater number of novel and valid compounds compared to other models, with these generated compounds exhibiting properties similar to those of real molecular data. These results indicate that our proposed method is highly effective in designing drugs targeting specific proteins.

Pleuroparenchymal fibroelastosis after hematopoietic stem cell transplantation in children: a propensity score-matched analysis.

OBJECTIVES: To investigate the incidence, risk factors, and clinical outcomes of pleuroparenchymal fibroelastosis (PPFE) in pediatric hematopoietic stem cell transplantation (HSCT) recipients. METHODS: This single-center, retrospective, case-control study included 738 consecutive patients who underwent chest CT more than 3 months after HSCT. We identified patients who fulfilled the diagnostic criteria for PPFE and assessed their clinical characteristics and radiologic findings. Propensity score-matched analysis was performed using four covariates (age, sex, HSCT type, and primary disease). The risk factors and clinical outcomes of PPFE were analyzed using the Fine and Gray regression model and stratified log-rank test in the matched groups. RESULTS: PPFE was identified in 4% (31/738, 8.3 ± 3.1 years, 15 males) of the pediatric HSCT recipients with a median time of 2.7 years after HSCT, and it occurred following allogeneic (5%, 15/317), autologous (4%, 15/379), or both (2%, 1/42). Matching yielded 30 and 130 cases in the PPFE and control groups, respectively. The PPFE group showed more frequent late-onset noninfectious pulmonary complications (LONIPCs) and pneumonia more than 3 months after HSCT (p < 0.05). Multivariable analysis showed a significantly higher risk of PPFE in HSCT recipients who had pneumonia more than 3 months after HSCT (hazard ratio = 10.78 [95% confidence interval: 4.29, 27.13], p < 0.001). The PPFE group showed higher mortality (73%, 22/30) and poorer median overall survival (6.8 years [95% confidence interval: 4.1, 9.5]) than the control group (p < 0.001). CONCLUSIONS: PPFE represents a severe type of LONIPC after HSCT. HSCT recipients with pneumonia after HSCT may have an increased risk of PPFE. KEY POINTS: • The incidence of pleuroparenchymal fibroelastosis is not negligible (4%), and it can occur after either allogeneic or autologous hematopoietic stem cell transplantation. • Pleuroparenchymal fibroelastosis after hematopoietic stem cell transplantation showed poor outcome with a high mortality rate of 73% and median overall survival of 6.8 years. • After hematopoietic stem cell transplantation, pneumonia may increase the risk of pleuroparenchymal fibroelastosis development in children. • Lung biopsy should not be indicated in patients with pleuroparenchymal fibroelastosis findings on chest CT as it can cause refractory pneumothorax without helping the diagnosis.

Deep Learning for Identifying Promising Drug Candidates in Drug-Phospholipid Complexes.

Drug-phospholipid complexing is a promising formulation technology for improving the low bioavailability of active pharmaceutical ingredients (APIs). However, identifying whether phospholipid and candidate drug can form a complex through in vitro tests can be costly and time-consuming due to the physicochemical properties and experimental environment. In a previous study, the authors developed seven machine learning models to predict drug-phospholipid complex formation, and the lightGBM model demonstrated the best performance. However, the previous study was unable to sufficiently address the degradation of test performance caused by the small size of the training data with class imbalance, and it had the limitation of considering only machine learning techniques. To overcome these limitations, we propose a new deep learning-based prediction model that employs variational autoencoder (VAE) and principal component analysis (PCA) techniques to improve prediction performance. The model uses a multi-layer one-dimensional convolutional neural network (CNN) with a skip connection to effectively capture the complex relationship between drugs and lipid molecules. The computer simulation results demonstrate that our proposed model performs better than the previous model in all performance metrics.

Gd-EOB-DTPA MRI for focal nodular hyperplasia-like lesions in pediatric cancer survivors.

OBJECTIVES: To investigate the hepatobiliary enhancement patterns of gadoxetic acid (Gd-EOB-DTPA) MRI and the temporal evolution of focal nodular hyperplasia (FNH)-like lesions in pediatric cancer survivors. METHODS: We retrospectively included pediatric cancer survivors who had new liver lesions detected during surveillance imaging and who were diagnosed with FNH-like lesions by Gd-EOB-DTPA MRI without the aid of a hepatobiliary phase. The hepatobiliary enhancement patterns of FNH-like lesions were categorized as homogeneous hyperintense/isointense, heterogeneous hyperintense, and ring-like enhancement. Temporal changes in the FNH-like lesions were evaluated by follow-up Gd-EOB-DTPA MRI. Statistical analyses included one-way analysis of variance and Spearman's rank correlation test. RESULTS: A total of 132 radiologically diagnosed FNH-like lesions in 18 patients showed the three different hepatobiliary enhancement patterns: homogeneous hyperintense/isointense (n = 65, 49%), heterogeneous hyperintense (n = 24, 18%), and ring-like enhancement (n = 43, 33%). A weak positive correlation was found between the lesion size and the hepatobiliary enhancement pattern (p = 0.015). Follow-up MRI showed alterations in the size and number of 55 FNHs in 8 patients, including stable size (n = 15, 27%), increased size (n = 17, 31%), decreased size (n = 11, 20%), disappearance (n = 12, 22%), and 74 new lesions (5 patients, 63%). CONCLUSIONS: FNH-like lesions in pediatric cancer survivors showed three different hepatobiliary enhancement patterns and various temporal changes. Recognition of the radiological characteristics of FNH-like lesions may avoid unnecessary invasive procedures and reduce patients/parents' anxiety. KEY POINTS: • FNH-like lesions in pediatric cancer survivors showed three different hepatobiliary enhancement patterns. The most common was homogeneous hyperintense/isointense, followed by heterogeneous hyperintense, and ring-like enhancement. • FNH-like lesions in pediatric cancer survivors can show various temporal changes during follow-up.

Evaluation of the image quality and dose reduction in digital radiography with an advanced spatial noise reduction algorithm in pediatric patients.

OBJECTIVES: To evaluate whether the advanced spatial noise reduction (ASNR) algorithm installed in a digital radiography system generates acceptable images at a lower dose than a conventional denoising algorithm in pediatric patients. METHODS: Nine sets of 30 images of pediatric patients, classified under three protocols and three age groups, were retrospectively selected. Different levels of low-dose image sets of these 270 images were generated by a noise simulation tool after validation testing using phantoms. Each image set was obtained with both the ASNR and conventional algorithm, and grouped randomly and blinded. Three experienced pediatric radiologists were asked to pick the "image with optimum dose" among images of different dose levels with an ALARA (as low as reasonably achievable) perspective. Dose reduction rates for each protocol and age group were calculated, and entrance skin exposure (ESE) was calculated using the values of kVp and mAs, assuming a standard body depth for each age group. RESULTS: With the ASNR algorithm, estimated dose reduction rates were highest for abdominal radiographs (45.0%, 27.3%, and 24.3% in infants, children, and adolescents, respectively, p < 0.001). The mean dose reductions for all age groups in the abdominal, chest, and skull radiographs were 32.8%, 12.9%, and 23.2%, respectively (p < 0.001). Average of the calculated ESE was lower with the ASNR algorithm than with the conventional algorithm group (p < 0.001). CONCLUSIONS: The ASNR algorithm facilitated optimization of image quality with a higher reduction in radiation dose than the conventional algorithm, making it more acceptable for use in pediatric patients. KEY POINTS: •ASNR algorithm in DR system improves image quality via enhanced contrast and noise removal by estimating actual noise distribution based on a multi-scale noise covariance and frequency processing. •Noise simulation tool (NST) generating images of different dose levels can be used for evaluation of the optimum dose without unnecessary additional radiation exposure to pediatric patients. •Retrospective clinical study using NST showed that the ASNR algorithm enabled a higher reduction in radiation dose than the conventional algorithm in pediatric patients.

Factorial Validity of the Arabic Version of the Stress and Anxiety to Viral Epidemics-6 Items (SAVE-6) Scale among the General Population in Lebanon.

This study explored the psychometric properties of the Arabic version of the Stress and Anxiety to Viral Epidemics-6 items (SAVE-6) scale for assessing people's anxiety in response to the viral epidemic in Lebanon. The 406 participants responded voluntarily to the online survey that included the SAVE-6, Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9) tools. The single-structure SAVE-6 model showed good internal consistency (Cronbach's α = 0.773). The SAVE-6 scale also showed good convergent validity with the GAD-7 (Spearman's ρ = 0.42, P < 0.001) and PHQ-9 (ρ = 0.38, P < 0.001). Receiver operating characteristic (ROC) analysis revealed an Arabic SAVE-6 cut-off score of 12 points (area under the curve [AUC] = 0.753; sensitivity = 62.74%; specificity = 78.26%) for an at least mild degree of anxiety (GAD-7 score ≥ 5). The Arabic version of the SAVE-6 was a reliable, valid, and solely usable scale for measuring the anxiety response of the general population to the viral epidemic.

De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology.

BACKGROUND: High-resolution medical images that include facial regions can be used to recognize the subject's face when reconstructing 3-dimensional (3D)-rendered images from 2-dimensional (2D) sequential images, which might constitute a risk of infringement of personal information when sharing data. According to the Health Insurance Portability and Accountability Act (HIPAA) privacy rules, full-face photographic images and any comparable image are direct identifiers and considered as protected health information. Moreover, the General Data Protection Regulation (GDPR) categorizes facial images as biometric data and stipulates that special restrictions should be placed on the processing of biometric data. OBJECTIVE: This study aimed to develop software that can remove the header information from Digital Imaging and Communications in Medicine (DICOM) format files and facial features (eyes, nose, and ears) at the 2D sliced-image level to anonymize personal information in medical images. METHODS: A total of 240 cranial magnetic resonance (MR) images were used to train the deep learning model (144, 48, and 48 for the training, validation, and test sets, respectively, from the Alzheimer's Disease Neuroimaging Initiative [ADNI] database). To overcome the small sample size problem, we used a data augmentation technique to create 576 images per epoch. We used attention-gated U-net for the basic structure of our deep learning model. To validate the performance of the software, we adapted an external test set comprising 100 cranial MR images from the Open Access Series of Imaging Studies (OASIS) database. RESULTS: The facial features (eyes, nose, and ears) were successfully detected and anonymized in both test sets (48 from ADNI and 100 from OASIS). Each result was manually validated in both the 2D image plane and the 3D-rendered images. Furthermore, the ADNI test set was verified using Microsoft Azure's face recognition artificial intelligence service. By adding a user interface, we developed and distributed (via GitHub) software named "Deface program" for medical images as an open-source project. CONCLUSIONS: We developed deep learning-based software for the anonymization of MR images that distorts the eyes, nose, and ears to prevent facial identification of the subject in reconstructed 3D images. It could be used to share medical big data for secondary research while making both data providers and recipients compliant with the relevant privacy regulations.

Artificial Intelligence in Health Care: Current Applications and Issues.

In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health care field, numerous efforts are being made to implement the AI technology for practical medical treatments. With the rapid developments in machine learning algorithms and improvements in hardware performances, the AI technology is expected to play an important role in effectively analyzing and utilizing extensive amounts of health and medical data. However, the AI technology has various unique characteristics that are different from the existing health care technologies. Subsequently, there are a number of areas that need to be supplemented within the current health care system for the AI to be utilized more effectively and frequently in health care. In addition, the number of medical practitioners and public that accept AI in the health care is still low; moreover, there are various concerns regarding the safety and reliability of AI technology implementations. Therefore, this paper aims to introduce the current research and application status of AI technology in health care and discuss the issues that need to be resolved.

Outcome and risk factors associated with perirenal subcapsular fluid collections in extremely preterm infants with acute kidney injury.

OBJECTIVES: To investigate the incidence of, clinical outcome of, and risk factors for perirenal subcapsular fluid collections in extremely preterm infants with acute kidney injury (AKI). METHODS: Extremely preterm infants with AKI who underwent renal ultrasonography (US) during neonatal intensive care unit stay were classified into two groups according to the presence of a perirenal subcapsular fluid collection at US. Clinical outcome was compared, and relevant data were analysed, including demographics and comorbidities of the infants, as well as maternal demographics. The risk factor of perirenal subcapsular fluid in infants with AKI was tested with univariate and multivariate logistic regression analysis. RESULTS: A perirenal subcapsular fluid collection was detected in 7 of 56 (13%) extremely preterm infants with AKI (male to female ratio, 5:2; mean gestational age, 23.6 ± 1.4 weeks) and it appeared bilaterally in most cases (86%, 6/7). The mortality rate was higher in infants with perirenal subcapsular fluid collections and AKI (86%, 6/7) than with AKI alone (35%, 17/49) (p = 0.015). Infants with perirenal subcapsular fluid collections and AKI were of a lower gestational age, and more frequently showed episodes of intestinal perforation, use of medication having potential to impair renal function, and a history of maternal chorioamnionitis (p < 0.05). Multivariate analysis revealed a significantly higher risk for perirenal subcapsular fluid collections in extremely preterm infants who were treated with anti-fungal agents (OR, 13.2 (95% CI: 1.5, 119.4); p = 0.022). CONCLUSIONS: Although a perirenal subcapsular fluid collection occurred in a small proportion of extremely preterm infants with AKI, its presence was associated with high mortality. The use of anti-fungal agents was an independent risk factor for a perirenal subcapsular fluid collection. KEY POINTS: • A perirenal subcapsular fluid collection may occur in association with acute kidney injury. • A perirenal subcapsular fluid collection has a grave prognostic implication in extremely preterm infants. • The use of anti-fungal agent might be associated with perirenal subscapular fluid collections in critically ill extremely preterm infants with AKI.

Early US findings of biliary atresia in infants younger than 30 days.

PURPOSE: To investigate and compare ultrasound (US) findings for the diagnosis of biliary atresia (BA) in infants younger than 30 days with those of infants older than 30 days. MATERIALS AND METHODS: From 2000 to 2015, we reviewed hepatobiliary US images in 12 BA infants younger than 30 days (younger BA group) and 62 BA infants older than 30 days (older BA group) before Kasai procedure. Eight (67%) of younger BA group underwent follow-up US examinations before Kasai procedure. Our review of the images focused on triangular cord sign, gallbladder (GB) abnormalities, vascular changes, and signs of portal hypertension. RESULTS: The triangular cord sign was present in 17% of younger BA group and in 56% of older BA group (P=.024). GB abnormalities were commonly identified in both groups. The hepatic artery diameter was significantly smaller in younger BA group than in older BA group (P<.001). Signs of portal hypertension were less common in younger BA group (17%) than in older BA group (84%) (P<.001). Follow-up US of two infants in younger BA group showed a new appearance of the triangular cord sign. CONCLUSION: BA infants younger than 30 days showed atypical US findings compared with those older than 30 days. KEY POINTS: • BA infants younger than 30 days show atypical US findings. • GB abnormalities were common in both younger and older BA group. • Subsequent US examination may be helpful to diagnose BA in young infants.

Utilization of a Clinical Trial Management System for the Whole Clinical Trial Process as an Integrated Database: System Development.

BACKGROUND: Clinical trials pose potential risks in both communications and management due to the various stakeholders involved when performing clinical trials. The academic medical center has a responsibility and obligation to conduct and manage clinical trials while maintaining a sufficiently high level of quality, therefore it is necessary to build an information technology system to support standardized clinical trial processes and comply with relevant regulations. OBJECTIVE: The objective of the study was to address the challenges identified while performing clinical trials at an academic medical center, Asan Medical Center (AMC) in Korea, by developing and utilizing a clinical trial management system (CTMS) that complies with standardized processes from multiple departments or units, controlled vocabularies, security, and privacy regulations. METHODS: This study describes the methods, considerations, and recommendations for the development and utilization of the CTMS as a consolidated research database in an academic medical center. A task force was formed to define and standardize the clinical trial performance process at the site level. On the basis of the agreed standardized process, the CTMS was designed and developed as an all-in-one system complying with privacy and security regulations. RESULTS: In this study, the processes and standard mapped vocabularies of a clinical trial were established at the academic medical center. On the basis of these processes and vocabularies, a CTMS was built which interfaces with the existing trial systems such as the electronic institutional review board health information system, enterprise resource planning, and the barcode system. To protect patient data, the CTMS implements data governance and access rules, and excludes 21 personal health identifiers according to the Health Insurance Portability and Accountability Act (HIPAA) privacy rule and Korean privacy laws. Since December 2014, the CTMS has been successfully implemented and used by 881 internal and external users for managing 11,645 studies and 146,943 subjects. CONCLUSIONS: The CTMS was introduced in the Asan Medical Center to manage the large amounts of data involved with clinical trial operations. Inter- and intraunit control of data and resources can be easily conducted through the CTMS system. To our knowledge, this is the first CTMS developed in-house at an academic medical center side which can enhance the efficiency of clinical trial management in compliance with privacy and security laws.

Congenital Adrenal Neuroblastoma With and Without Cystic Change: Differentiating Features With an Emphasis on the of Value of Ultrasound.

OBJECTIVE: The purpose of this study was to compare the features of congenital adrenal neuroblastomas with and without cystic changes and to emphasize the value of ultrasound in the diagnostic evaluation of cystic congenital adrenal neuroblastoma. MATERIALS AND METHODS: A total of 41 patients with surgically confirmed congenital adrenal neuroblastoma were enrolled. We divided the patients into two groups according to presence or absence of cystic change in the tumor, as determined from the initial ultrasound findings. Clinical and laboratory findings, disease stage, and patient outcome were investigated with a statistical comparison between the two groups. The imaging findings for cystic congenital adrenal neuroblastoma were reviewed to compare the additional diagnostic value of CT and MRI when paired with ultrasound. RESULTS: There were 22 patients (54%) in the group without cystic changes and 19 patients (46%) in the group with cystic changes. Prenatal detection and absence of metastasis were significantly more common in the cystic group than in the noncystic group (p < 0.05). Sensitivities of tumor marker levels were also significantly lower in the cystic group. Patient outcome was excellent, and there was no significant difference between the groups. With regard to imaging of cystic congenital adrenal neuroblastoma, in the 15 cases in which CT or MRI was paired with ultrasound, no additional diagnostic information was discerned with CT or MRI. CONCLUSION: Nearly one-half of congenital adrenal neuroblastomas are cystic, and these tumors have clinical and laboratory features that distinguish them from noncystic congenital adrenal neuroblastoma. Diagnostic tests, including CT, MRI, and assessment of tumor markers, have low diagnostic value in the evaluation of cystic congenital adrenal neuroblastoma.

Knowledge and Perception about Clinical Research Shapes Behavior: Face to Face Survey in Korean General Public.

Considering general public as potential patients, identifying factors that hinder public participation poses great importance, especially in a research environment where demands for clinical trial participants outpace the supply. Hence, the aim of this study was to evaluate knowledge and perception about clinical research in general public. A total of 400 Seoul residents with no previous experience of clinical trial participation were selected, as representative of population in Seoul in terms of age and sex. To minimize selection bias, every fifth passer-by was invited to interview, and if in a cluster, person on the very right side was asked. To ensure the uniform use of survey, written instructions have been added to the questionnaire. Followed by pilot test in 40 subjects, the survey was administered face-to-face in December 2014. To investigate how perception shapes behavior, we compared perception scores in those who expressed willingness to participate and those who did not. Remarkably higher percentage of responders stated that they have heard of clinical research, and knew someone who participated (both, P < 0.001) compared to India. Yet, the percentage of responders expressed willingness to participate was 39.3%, a significantly lower rate than the result of the India (58.9% vs. 39.3%, P < 0.001). Treatment benefit was the single most influential reason for participation, followed by financial gain. Concern about safety was the main reason for refusal, succeeded by fear and lack of trust. Public awareness and educational programs addressing these negative perceptions and lack of knowledge will be effective in enhancing public engaged in clinical research.

Diagnosis of neonatal ovarian torsion: Emphasis on prenatal and postnatal sonographic findings.

PURPOSE: Our aim was to retrospectively review the imaging findings of patients with neonatal ovarian torsion, emphasizing prenatal and postnatal sonographic findings. METHODS: Eleven patients who had had neonatal ovarian torsion diagnosed surgically (n = 9) or clinicoradiologically (n = 2) were enrolled. Prenatal and postnatal sonographic features, including sequential postnatal change, were reviewed. Clinical and pathologic features were also investigated. RESULTS: All patients except one had a fetal ovarian cyst (mean, 5.3 cm) detected on third-trimester sonography, either simple (n = 6) or complex (n = 4). In all 11 patients, initial postnatal sonography had revealed a complex cyst (mean, 4.7 cm) with intracystic clot or debris, the double-wall sign, a fluid-fluid level, and multiple septation. None of the patients had had symptoms or signs related to the ovarian torsion. Follow-up sonography in seven patients had revealed increased echogenicity of the cyst wall with frequent calcification and a decrease in size of the cyst. In two patients, the interval of the change in cyst position was noted, and autoamputation of the torsed ovary had been surgically confirmed. Serous cystadenoma had been identified in one patient. CONCLUSIONS: Neonatal ovarian torsion most commonly manifests as an asymptomatic complex cyst on sonography due to torsion of a fetal ovarian cyst. Serial monitoring of a fetal ovarian cyst for its resolution or changes in its appearance is mandatory for making an early diagnosis of torsion. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 44:290-297, 2016.

Clinical and imaging features of focal nodular hyperplasia in children.

OBJECTIVE: The purpose of this article is to review the clinical and imaging features of focal nodular hyperplasia (FNH) developed in children. MATERIALS AND METHODS: At a single institution, pediatric patients who underwent imaging studies and who had pathologically proven FNH were studied. Clinical characteristics, including presenting symptoms and signs and the presence of underlying disease, were reviewed from the medical records. Imaging features of FNHs, including the number, size, ultrasound echogenicity and vascularity, CT attenuation, MRI signal intensity and enhancement pattern, and the presence of a central scar, were evaluated. RESULTS: Twenty-five patients (11 boys and 14 girls; median age, 8.6 years) were found to have a solitary (n = 23) or multiple (n = 2) FNH lesions with a mean size of 4.9 cm (range, 1-10 cm). Multiple lesions were associated with small size of the lesions and history of malignancy treated by chemotherapy. Most patients were asymptomatic (n = 22). Biliary atresia was the most common underlying disease (n = 5). On ultrasound, FNHs most commonly appeared to be isoechoic and hypervascular. On dynamic CT and MRI, strong enhancement on the arterial phase and becoming isoattenuated or of isointense signal intensity on the portal or delayed phase was common. A central scar was usually noted in large lesions in about half the cases. CONCLUSION: Pediatric FNH is uncommon and usually is found incidentally in otherwise healthy children. However, it may occur in children who have underlying diseases, including biliary atresia. In addition, it can be encountered during surveillance of childhood cancer survivors with less common imaging features, including lack of a central scar and multiplicity.

Devastating metabolic brain disorders of newborns and young infants.

Metabolic disorders of the brain that manifest in the neonatal or early infantile period are usually associated with acute and severe illness and are thus referred to as devastating metabolic disorders. Most of these disorders may be classified as organic acid disorders, amino acid metabolism disorders, primary lactic acidosis, or fatty acid oxidation disorders. Each disorder has distinctive clinical, biochemical, and radiologic features. Early diagnosis is important both for prompt treatment to prevent death or serious sequelae and for genetic counseling. However, diagnosis is often challenging because many findings overlap and may mimic those of more common neonatal conditions, such as hypoxic-ischemic encephalopathy and infection. Ultrasonography (US) may be an initial screening method for the neonatal brain, and magnetic resonance (MR) imaging is the modality of choice for evaluating metabolic brain disorders. Although nonspecific imaging findings are common in early-onset metabolic disorders, characteristic patterns of brain involvement have been described for several disorders. In addition, diffusion-weighted images may be used to characterize edema during an acute episode of encephalopathy, and MR spectroscopy depicts changes in metabolites that may help diagnose metabolic disorders and assess response to treatment. Imaging findings, including those of advanced MR imaging techniques, must be closely reviewed. If one of these rare disorders is suspected, the appropriate biochemical test or analysis of the specific gene should be performed to confirm the diagnosis.