1.Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features
Harim KIM ; Jonghoon KIM ; Soohyun HWANG ; You Jin OH ; Joong Hyun AHN ; Min-Ji KIM ; Tae Hee HONG ; Sung Goo PARK ; Joon Young CHOI ; Hong Kwan KIM ; Jhingook KIM ; Sumin SHIN ; Ho Yun LEE
Cancer Research and Treatment 2025;57(1):57-69
Purpose:
This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns.
Materials and Methods:
As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features.
Results:
Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively).
Conclusion
Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.
2.Establishment of Local Diagnostic Reference Levels for Pediatric Neck CT at Nine University Hospitals in South Korea
Jisun HWANG ; Hee Mang YOON ; Jae-Yeon HWANG ; Young Hun CHOI ; Yun Young LEE ; So Mi LEE ; Young Jin RYU ; Sun Kyoung YOU ; Ji Eun PARK ; Seok Kee LEE
Korean Journal of Radiology 2025;26(1):65-74
Objective:
To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea.
Materials and Methods:
This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value.
Results:
A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older.
Conclusion
Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.
3.Establishment of Local Diagnostic Reference Levels for Pediatric Neck CT at Nine University Hospitals in South Korea
Jisun HWANG ; Hee Mang YOON ; Jae-Yeon HWANG ; Young Hun CHOI ; Yun Young LEE ; So Mi LEE ; Young Jin RYU ; Sun Kyoung YOU ; Ji Eun PARK ; Seok Kee LEE
Korean Journal of Radiology 2025;26(1):65-74
Objective:
To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea.
Materials and Methods:
This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value.
Results:
A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older.
Conclusion
Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.
4.Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features
Harim KIM ; Jonghoon KIM ; Soohyun HWANG ; You Jin OH ; Joong Hyun AHN ; Min-Ji KIM ; Tae Hee HONG ; Sung Goo PARK ; Joon Young CHOI ; Hong Kwan KIM ; Jhingook KIM ; Sumin SHIN ; Ho Yun LEE
Cancer Research and Treatment 2025;57(1):57-69
Purpose:
This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns.
Materials and Methods:
As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features.
Results:
Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively).
Conclusion
Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.
5.Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features
Harim KIM ; Jonghoon KIM ; Soohyun HWANG ; You Jin OH ; Joong Hyun AHN ; Min-Ji KIM ; Tae Hee HONG ; Sung Goo PARK ; Joon Young CHOI ; Hong Kwan KIM ; Jhingook KIM ; Sumin SHIN ; Ho Yun LEE
Cancer Research and Treatment 2025;57(1):57-69
Purpose:
This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns.
Materials and Methods:
As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features.
Results:
Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively).
Conclusion
Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.
6.Establishment of Local Diagnostic Reference Levels for Pediatric Neck CT at Nine University Hospitals in South Korea
Jisun HWANG ; Hee Mang YOON ; Jae-Yeon HWANG ; Young Hun CHOI ; Yun Young LEE ; So Mi LEE ; Young Jin RYU ; Sun Kyoung YOU ; Ji Eun PARK ; Seok Kee LEE
Korean Journal of Radiology 2025;26(1):65-74
Objective:
To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea.
Materials and Methods:
This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value.
Results:
A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older.
Conclusion
Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.
7.Establishment of Local Diagnostic Reference Levels for Pediatric Neck CT at Nine University Hospitals in South Korea
Jisun HWANG ; Hee Mang YOON ; Jae-Yeon HWANG ; Young Hun CHOI ; Yun Young LEE ; So Mi LEE ; Young Jin RYU ; Sun Kyoung YOU ; Ji Eun PARK ; Seok Kee LEE
Korean Journal of Radiology 2025;26(1):65-74
Objective:
To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea.
Materials and Methods:
This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value.
Results:
A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older.
Conclusion
Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.
8.Establishment of Local Diagnostic Reference Levels for Pediatric Neck CT at Nine University Hospitals in South Korea
Jisun HWANG ; Hee Mang YOON ; Jae-Yeon HWANG ; Young Hun CHOI ; Yun Young LEE ; So Mi LEE ; Young Jin RYU ; Sun Kyoung YOU ; Ji Eun PARK ; Seok Kee LEE
Korean Journal of Radiology 2025;26(1):65-74
Objective:
To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea.
Materials and Methods:
This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value.
Results:
A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older.
Conclusion
Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.
9.Clinical data on treatment regimen and use of medication among patients with hemophilia B in Korea
Young Shil PARK ; Ji Kyoung PARK ; Jeong A PARK ; Hee Jo BAEK ; Jae Hee LEE ; Chur Woo YOU ; Chuhl Joo LYU ; Eun Jin CHOI
Blood Research 2024;59():27-
Background:
To investigate the clinical treatment status, such as treatment regimen, bleeding events, and drug dose, in patients with hemophilia B in South Korea.
Methods:
In this retrospective chart review, data of patients with hemophilia B from eight university hospitals were collected. Demographic and clinical data, treatment data, such as regimen and number of injections, dose of factor IX concentrate, and bleeding data were reviewed. Descriptive analyses were performed with annual data for 2019, 2020, and 2021, as well as the three years consecutively.
Results:
The medical records of 150 patients with hemophilia B between January 1, 2019, and December 31, 2021, were collected. Among these, 72 (48.0%) were severe, 47 (31.3%) were moderate, and 28 (18.7%) were mild. The results showed approximately two times more patients receiving prophylaxis as those receiving on-demand therapy, with 66.1% of patients receiving prophylaxis in 2019, 64.9% in 2020, and 72.1% in 2021. Annualized bleeding rates were 2.2% (± 3.1) in 2019, 1.8% (± 3.0) in 2020, and 1.8% (± 2.9) in 2021 among patients receiving prophylaxis.For the doses of factor IX concentrate, patients receiving prophylaxis received an average of 41.6 (± 11.9) IU/Kg/Injection in 2019, 45.7 (± 12.9) IU/Kg/Injection in 2020, and 60.1 (± 24.0) IU/Kg/Injection in 2021.
Conclusions
Clinically, prophylaxis is more prevalent than reported. Based on insights gained from current clinical evidence, it is expected that the unmet medical needs of patients can be identified, and physicians can evaluate the status of patients and actively manage hemophilia B using more effective treatment strategies.
10.Metabolic Dysfunction-Associated Steatotic Liver Disease in Type 2 Diabetes Mellitus: A Review and Position Statement of the Fatty Liver Research Group of the Korean Diabetes Association
Jaehyun BAE ; Eugene HAN ; Hye Won LEE ; Cheol-Young PARK ; Choon Hee CHUNG ; Dae Ho LEE ; Eun-Hee CHO ; Eun-Jung RHEE ; Ji Hee YU ; Ji Hyun PARK ; Ji-Cheol BAE ; Jung Hwan PARK ; Kyung Mook CHOI ; Kyung-Soo KIM ; Mi Hae SEO ; Minyoung LEE ; Nan-Hee KIM ; So Hun KIM ; Won-Young LEE ; Woo Je LEE ; Yeon-Kyung CHOI ; Yong-ho LEE ; You-Cheol HWANG ; Young Sang LYU ; Byung-Wan LEE ; Bong-Soo CHA ;
Diabetes & Metabolism Journal 2024;48(6):1015-1028
Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

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