1.Korean Practice Guidelines for Gastric Cancer 2024: An Evidence-based, Multidisciplinary Approach (Update of 2022 Guideline)
In-Ho KIM ; Seung Joo KANG ; Wonyoung CHOI ; An Na SEO ; Bang Wool EOM ; Beodeul KANG ; Bum Jun KIM ; Byung-Hoon MIN ; Chung Hyun TAE ; Chang In CHOI ; Choong-kun LEE ; Ho Jung AN ; Hwa Kyung BYUN ; Hyeon-Su IM ; Hyung-Don KIM ; Jang Ho CHO ; Kyoungjune PAK ; Jae-Joon KIM ; Jae Seok BAE ; Jeong Il YU ; Jeong Won LEE ; Jungyoon CHOI ; Jwa Hoon KIM ; Miyoung CHOI ; Mi Ran JUNG ; Nieun SEO ; Sang Soo EOM ; Soomin AHN ; Soo Jin KIM ; Sung Hak LEE ; Sung Hee LIM ; Tae-Han KIM ; Hye Sook HAN ; On behalf of The Development Working Group for the Korean Practice Guideline for Gastric Cancer 2024
Journal of Gastric Cancer 2025;25(1):5-114
Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.
2.Korean Practice Guidelines for Gastric Cancer 2024: An Evidence-based, Multidisciplinary Approach (Update of 2022 Guideline)
In-Ho KIM ; Seung Joo KANG ; Wonyoung CHOI ; An Na SEO ; Bang Wool EOM ; Beodeul KANG ; Bum Jun KIM ; Byung-Hoon MIN ; Chung Hyun TAE ; Chang In CHOI ; Choong-kun LEE ; Ho Jung AN ; Hwa Kyung BYUN ; Hyeon-Su IM ; Hyung-Don KIM ; Jang Ho CHO ; Kyoungjune PAK ; Jae-Joon KIM ; Jae Seok BAE ; Jeong Il YU ; Jeong Won LEE ; Jungyoon CHOI ; Jwa Hoon KIM ; Miyoung CHOI ; Mi Ran JUNG ; Nieun SEO ; Sang Soo EOM ; Soomin AHN ; Soo Jin KIM ; Sung Hak LEE ; Sung Hee LIM ; Tae-Han KIM ; Hye Sook HAN ; On behalf of The Development Working Group for the Korean Practice Guideline for Gastric Cancer 2024
Journal of Gastric Cancer 2025;25(1):5-114
Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.
3.Anti-Amyloid Imaging Abnormality in the Era of Anti-Amyloid Beta Monoclonal Antibodies:Recent Updates for the Radiologist
So Yeong JEONG ; Chong Hyun SUH ; Jae-Sung LIM ; Yangsean CHOI ; Ho Sung KIM ; Sang Joon KIM ; Jae-Hong LEE
Journal of the Korean Society of Radiology 2025;86(1):17-33
Lecanemab and donanemab have received full U.S. Food and Drug Administration (FDA) approval, and subsequently, lecanemab has been approved by the Korean FDA and it has recently entered commercial use in Korea. This has increased interest in anti-amyloid immunotherapy for Alzheimer’s disease. Anti-amyloid immunotherapy has shown potential to modify the progression of the disease by specifically binding to amyloid β, a key pathological product in Alzheimer’s disease, and eliminating accumulated amyloid plaques in the brain. However, this treatment can be accompanied by a side-effect, amyloid-related imaging abnormalities (ARIA), which requires periodic monitoring by MRI. It is crucial to detect ARIA and accurately assess the severity by radiology. The role of the radiologist is important in this context, requiring proficiency in basic knowledge of ARIA, and in diagnosing/evaluating ARIA. This review aims to comprehensively cover aspects of ARIA, including its definition, pathophysiology, incidence, risk factors, assessment of severity by radiology, differential diagnosis, and management.
5.Anti-Amyloid Imaging Abnormality in the Era of Anti-Amyloid Beta Monoclonal Antibodies:Recent Updates for the Radiologist
So Yeong JEONG ; Chong Hyun SUH ; Jae-Sung LIM ; Yangsean CHOI ; Ho Sung KIM ; Sang Joon KIM ; Jae-Hong LEE
Journal of the Korean Society of Radiology 2025;86(1):17-33
Lecanemab and donanemab have received full U.S. Food and Drug Administration (FDA) approval, and subsequently, lecanemab has been approved by the Korean FDA and it has recently entered commercial use in Korea. This has increased interest in anti-amyloid immunotherapy for Alzheimer’s disease. Anti-amyloid immunotherapy has shown potential to modify the progression of the disease by specifically binding to amyloid β, a key pathological product in Alzheimer’s disease, and eliminating accumulated amyloid plaques in the brain. However, this treatment can be accompanied by a side-effect, amyloid-related imaging abnormalities (ARIA), which requires periodic monitoring by MRI. It is crucial to detect ARIA and accurately assess the severity by radiology. The role of the radiologist is important in this context, requiring proficiency in basic knowledge of ARIA, and in diagnosing/evaluating ARIA. This review aims to comprehensively cover aspects of ARIA, including its definition, pathophysiology, incidence, risk factors, assessment of severity by radiology, differential diagnosis, and management.
7.Korean Practice Guidelines for Gastric Cancer 2024: An Evidence-based, Multidisciplinary Approach (Update of 2022 Guideline)
In-Ho KIM ; Seung Joo KANG ; Wonyoung CHOI ; An Na SEO ; Bang Wool EOM ; Beodeul KANG ; Bum Jun KIM ; Byung-Hoon MIN ; Chung Hyun TAE ; Chang In CHOI ; Choong-kun LEE ; Ho Jung AN ; Hwa Kyung BYUN ; Hyeon-Su IM ; Hyung-Don KIM ; Jang Ho CHO ; Kyoungjune PAK ; Jae-Joon KIM ; Jae Seok BAE ; Jeong Il YU ; Jeong Won LEE ; Jungyoon CHOI ; Jwa Hoon KIM ; Miyoung CHOI ; Mi Ran JUNG ; Nieun SEO ; Sang Soo EOM ; Soomin AHN ; Soo Jin KIM ; Sung Hak LEE ; Sung Hee LIM ; Tae-Han KIM ; Hye Sook HAN ; On behalf of The Development Working Group for the Korean Practice Guideline for Gastric Cancer 2024
Journal of Gastric Cancer 2025;25(1):5-114
Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.
8.Anti-Amyloid Imaging Abnormality in the Era of Anti-Amyloid Beta Monoclonal Antibodies:Recent Updates for the Radiologist
So Yeong JEONG ; Chong Hyun SUH ; Jae-Sung LIM ; Yangsean CHOI ; Ho Sung KIM ; Sang Joon KIM ; Jae-Hong LEE
Journal of the Korean Society of Radiology 2025;86(1):17-33
Lecanemab and donanemab have received full U.S. Food and Drug Administration (FDA) approval, and subsequently, lecanemab has been approved by the Korean FDA and it has recently entered commercial use in Korea. This has increased interest in anti-amyloid immunotherapy for Alzheimer’s disease. Anti-amyloid immunotherapy has shown potential to modify the progression of the disease by specifically binding to amyloid β, a key pathological product in Alzheimer’s disease, and eliminating accumulated amyloid plaques in the brain. However, this treatment can be accompanied by a side-effect, amyloid-related imaging abnormalities (ARIA), which requires periodic monitoring by MRI. It is crucial to detect ARIA and accurately assess the severity by radiology. The role of the radiologist is important in this context, requiring proficiency in basic knowledge of ARIA, and in diagnosing/evaluating ARIA. This review aims to comprehensively cover aspects of ARIA, including its definition, pathophysiology, incidence, risk factors, assessment of severity by radiology, differential diagnosis, and management.
10.Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study
Sang Won PARK ; Na Young YEO ; Seonguk KANG ; Taejun HA ; Tae-Hoon KIM ; DooHee LEE ; Dowon KIM ; Seheon CHOI ; Minkyu KIM ; DongHoon LEE ; DoHyeon KIM ; Woo Jin KIM ; Seung-Joon LEE ; Yeon-Jeong HEO ; Da Hye MOON ; Seon-Sook HAN ; Yoon KIM ; Hyun-Soo CHOI ; Dong Kyu OH ; Su Yeon LEE ; MiHyeon PARK ; Chae-Man LIM ; Jeongwon HEO ; On behalf of the Korean Sepsis Alliance (KSA) Investigators
Journal of Korean Medical Science 2024;39(5):e53-
Background:
Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department.
Methods:
This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP).
Results:
Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results.
Conclusion
Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

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