1.Interpretation, Reporting, Imaging-Based Workups, and Surveillance of Incidentally Detected Gallbladder Polyps and Gallbladder Wall Thickening: 2025 Recommendations From the Korean Society of Abdominal Radiology
Won CHANG ; Sunyoung LEE ; Yeun-Yoon KIM ; Jin Young PARK ; Sun Kyung JEON ; Jeong Eun LEE ; Jeongin YOO ; Seungchul HAN ; So Hyun PARK ; Jae Hyun KIM ; Hyo Jung PARK ; Jeong Hee YOON
Korean Journal of Radiology 2025;26(2):102-134
Incidentally detected gallbladder polyps (GBPs) and gallbladder wall thickening (GBWT) are frequently encountered in clinical practice. However, characterizing GBPs and GBWT in asymptomatic patients can be challenging and may result in overtreatment, including unnecessary follow-ups or surgeries. The Korean Society of Abdominal Radiology (KSAR) Clinical Practice Guideline Committee has developed expert recommendations that focus on standardized imaging interpretation and follow-up strategies for both GBPs and GBWT, with support from the Korean Society of Radiology and KSAR. These guidelines, which address 24 key questions, aim to standardize the approach for the interpretation of imaging findings, reporting, imaging-based workups, and surveillance of incidentally detected GBPs and GBWT. This recommendation promotes evidence-based practice, facilitates communication between radiologists and referring physicians, and reduces unnecessary interventions.
2.Changing Gadolinium-Based Contrast Agents to Prevent Recurrent Acute Adverse Drug Reactions: 6-Year Cohort Study Using Propensity Score Matching
Min Woo HAN ; Chong Hyun SUH ; Pyeong Hwa KIM ; Seonok KIM ; Ah Young KIM ; Kyung-Hyun DO ; Jeong Hyun LEE ; Dong-Il GWON ; Ah Young JUNG ; Choong Wook LEE
Korean Journal of Radiology 2025;26(2):204-204
3.Implementation of a Learning Management System at Yonsei University College of Medicine
Hanna JUNG ; Hangil KIM ; Hyung-Jin RHEE ; Sang Ah LEE ; Shinki AN ; Young Han LEE
Korean Medical Education Review 2025;27(1):40-51
This paper details the development and implementation of Yonsei Medical E-Learning System 3.0 (YES 3.0), a new learning management system (LMS) for Yonsei University College of Medicine. Driven by the need to adapt to a rapidly changing medical education landscape, YES 3.0 addresses the previous system’s limitations and incorporates advanced features designed to improve learning experiences and educational outcomes. The development process involved extensive collaboration among faculty, students, staff, and the system developer, ensuring the system's alignment with the unique needs of the medical education environment. YES 3.0 features real-time monitoring of learning progress, comprehensive evaluation and grade management, personalized learning path recommendations, effective learner history management, and interview/guidance management functionalities. The system also supports the newly revised CDP2023 (Curriculum Development Project 2023) curriculum, with integrated learning across all courses and a strengthened scholarly advanced course. By automating and streamlining various educational processes, YES 3.0 enables maximized learning efficiency, promotes learner-centered education, and supports the cultivation of future medical professionals equipped to navigate the evolving healthcare environment. Implementing the system is expected to have positive impacts on both educational and economic aspects, contributing to the advancement of medical education at Yonsei University College of Medicine. This study also aims to offer insights and expected outcomes that can serve as a reference for other medical schools in adopting and operating LMS, ultimately providing useful information to educators considering establishing a digital learning environment.
4.The Effect of Postnatal Systemic Corticosteroid on Neurodevelopmental Outcome in Very Low Birth Weight Preterm Infants
Joo Yun YANG ; Young Min YOUN ; Jung In KANG ; Ye Jin HAN ; Do Kyung LEE ; Hyun Kyung BAE ; So-Yeon SHIM
Neonatal Medicine 2025;32(1):10-20
Purpose:
This study aimed to investigate the effects of postnatal systemic corticosteroids on neurodevelopment in very low birth weight (VLBW) preterm infants.
Methods:
This was a population-based study of the Korean Neonatal Network of VLBW infant born at 23+0 and 31+6 weeks of gestation between 2013 and 2020. VLBW preterm infants assessed using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III) at 18–24 months of corrected age and 3 years of age were enrolled. The primary outcomes were BSID-III scores and neurodevelopmental delays, with scores of <85. Socioeconomic status and clinical variables were adjusted for using multivariate regression analyses.
Results:
In total, 517 infants were enrolled in this study. Among the 216 (41.8%) infants who received postnatal systemic corticosteroids, the rate of cognitive delay was significantly higher at 18–24 months of corrected age than at 3 years of age. The rates of language and motor delays were significantly higher both at 18–24 months of corrected age and at 3 years of age. When multivariate logistic regression was performed, postnatal systemic corticosteroid use was significantly associated with cognitive delay at 18–24 months of corrected age, but not at 3 years of age. There was no significant association between postnatal systemic corticosteroid use and language or motor delay at 18-24 months of corrected age or at 3 years of age after multivariate logistic regression.
Conclusion
Postnatal systemic corticosteroid use in VLBW preterm infants increased the risk of cognitive delay at 18–24 months of corrected age, but not at 3 years.
5.Prospective Evaluation of Various Ultrasound Parameters for Assessing Renal Allograft Rejection Subtypes: Elasticity and Dispersion as Diagnostic Tools
Yeji KWON ; Jongjin YOON ; Dae Chul JUNG ; Young Taik OH ; Kyunghwa HAN ; Minsun JUNG ; Byung Chul KANG
Yonsei Medical Journal 2025;66(4):249-258
Purpose:
Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection.
Materials and Methods:
Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations.
Results:
Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers.
Conclusion
Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.
6.Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data
Changho HAN ; Yun Jung JUNG ; Ji Eun PARK ; Wou Young CHUNG ; Dukyong YOON
Yonsei Medical Journal 2025;66(2):121-130
Purpose:
Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival.
Materials and Methods:
Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices.
Results:
Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables.
Conclusion
Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.
7.Interpretation, Reporting, Imaging-Based Workups, and Surveillance of Incidentally Detected Gallbladder Polyps and Gallbladder Wall Thickening: 2025 Recommendations From the Korean Society of Abdominal Radiology
Won CHANG ; Sunyoung LEE ; Yeun-Yoon KIM ; Jin Young PARK ; Sun Kyung JEON ; Jeong Eun LEE ; Jeongin YOO ; Seungchul HAN ; So Hyun PARK ; Jae Hyun KIM ; Hyo Jung PARK ; Jeong Hee YOON
Korean Journal of Radiology 2025;26(2):102-134
Incidentally detected gallbladder polyps (GBPs) and gallbladder wall thickening (GBWT) are frequently encountered in clinical practice. However, characterizing GBPs and GBWT in asymptomatic patients can be challenging and may result in overtreatment, including unnecessary follow-ups or surgeries. The Korean Society of Abdominal Radiology (KSAR) Clinical Practice Guideline Committee has developed expert recommendations that focus on standardized imaging interpretation and follow-up strategies for both GBPs and GBWT, with support from the Korean Society of Radiology and KSAR. These guidelines, which address 24 key questions, aim to standardize the approach for the interpretation of imaging findings, reporting, imaging-based workups, and surveillance of incidentally detected GBPs and GBWT. This recommendation promotes evidence-based practice, facilitates communication between radiologists and referring physicians, and reduces unnecessary interventions.
8.Changing Gadolinium-Based Contrast Agents to Prevent Recurrent Acute Adverse Drug Reactions: 6-Year Cohort Study Using Propensity Score Matching
Min Woo HAN ; Chong Hyun SUH ; Pyeong Hwa KIM ; Seonok KIM ; Ah Young KIM ; Kyung-Hyun DO ; Jeong Hyun LEE ; Dong-Il GWON ; Ah Young JUNG ; Choong Wook LEE
Korean Journal of Radiology 2025;26(2):204-204
9.Implementation of a Learning Management System at Yonsei University College of Medicine
Hanna JUNG ; Hangil KIM ; Hyung-Jin RHEE ; Sang Ah LEE ; Shinki AN ; Young Han LEE
Korean Medical Education Review 2025;27(1):40-51
This paper details the development and implementation of Yonsei Medical E-Learning System 3.0 (YES 3.0), a new learning management system (LMS) for Yonsei University College of Medicine. Driven by the need to adapt to a rapidly changing medical education landscape, YES 3.0 addresses the previous system’s limitations and incorporates advanced features designed to improve learning experiences and educational outcomes. The development process involved extensive collaboration among faculty, students, staff, and the system developer, ensuring the system's alignment with the unique needs of the medical education environment. YES 3.0 features real-time monitoring of learning progress, comprehensive evaluation and grade management, personalized learning path recommendations, effective learner history management, and interview/guidance management functionalities. The system also supports the newly revised CDP2023 (Curriculum Development Project 2023) curriculum, with integrated learning across all courses and a strengthened scholarly advanced course. By automating and streamlining various educational processes, YES 3.0 enables maximized learning efficiency, promotes learner-centered education, and supports the cultivation of future medical professionals equipped to navigate the evolving healthcare environment. Implementing the system is expected to have positive impacts on both educational and economic aspects, contributing to the advancement of medical education at Yonsei University College of Medicine. This study also aims to offer insights and expected outcomes that can serve as a reference for other medical schools in adopting and operating LMS, ultimately providing useful information to educators considering establishing a digital learning environment.
10.The Effect of Postnatal Systemic Corticosteroid on Neurodevelopmental Outcome in Very Low Birth Weight Preterm Infants
Joo Yun YANG ; Young Min YOUN ; Jung In KANG ; Ye Jin HAN ; Do Kyung LEE ; Hyun Kyung BAE ; So-Yeon SHIM
Neonatal Medicine 2025;32(1):10-20
Purpose:
This study aimed to investigate the effects of postnatal systemic corticosteroids on neurodevelopment in very low birth weight (VLBW) preterm infants.
Methods:
This was a population-based study of the Korean Neonatal Network of VLBW infant born at 23+0 and 31+6 weeks of gestation between 2013 and 2020. VLBW preterm infants assessed using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III) at 18–24 months of corrected age and 3 years of age were enrolled. The primary outcomes were BSID-III scores and neurodevelopmental delays, with scores of <85. Socioeconomic status and clinical variables were adjusted for using multivariate regression analyses.
Results:
In total, 517 infants were enrolled in this study. Among the 216 (41.8%) infants who received postnatal systemic corticosteroids, the rate of cognitive delay was significantly higher at 18–24 months of corrected age than at 3 years of age. The rates of language and motor delays were significantly higher both at 18–24 months of corrected age and at 3 years of age. When multivariate logistic regression was performed, postnatal systemic corticosteroid use was significantly associated with cognitive delay at 18–24 months of corrected age, but not at 3 years of age. There was no significant association between postnatal systemic corticosteroid use and language or motor delay at 18-24 months of corrected age or at 3 years of age after multivariate logistic regression.
Conclusion
Postnatal systemic corticosteroid use in VLBW preterm infants increased the risk of cognitive delay at 18–24 months of corrected age, but not at 3 years.

Result Analysis
Print
Save
E-mail