1.Prospective Evaluation of Accelerated Brain MRI Using Deep Learning-Based Reconstruction: Simultaneous Application to 2D Spin-Echo and 3D Gradient-Echo Sequences
Kyu Sung CHOI ; Chanrim PARK ; Ji Ye LEE ; Kyung Hoon LEE ; Young Hun JEON ; Inpyeong HWANG ; Roh Eul YOO ; Tae Jin YUN ; Mi Ji LEE ; Keun-Hwa JUNG ; Koung Mi KANG
Korean Journal of Radiology 2025;26(1):54-64
Objective:
To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials and Methods:
This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed.
Results:
Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29).
Conclusion
Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.
2.Prevalence and Factors Influencing Behavioral Addictions among School Adolescents: A Study in the Gwangju-Jeonnam Region
Narae KIM ; Bo-Hyun YOON ; Hyunju YUN ; Hyoung-Yeon KIM ; Ha-Ran JUNG ; Yuran JEONG ; Suhee PARK ; Young-Hwa SEA
Mood and Emotion 2025;23(1):11-20
Background:
The aim of this study is to evaluate the prevalence and associated psychosocial factors of behavioral addictions among school adolescents living in the Gwangju and Jeonnam regions in Korea.
Methods:
A self-reported survey was conducted from December 4, 2023, to January 31, 2024, including 855 middle and high school students residing in the Gwangju-Jeonnam regions. Aside from the information on demographic characteristics, data on depression, anxiety, Internet gaming addiction, gambling problems, and resilience was obtained.
Results:
The prevalence of Internet gaming addiction among adolescents was 5.4%, while the prevalence of gambling problems was 3.3%. The male adolescents had a significantly higher risk of behavioral addiction compared with the female adolescents. The logistic regression analysis revealed that male and depression were significant risk factors for Internet gaming addiction. For gambling problems, male was identified as a significant risk factor.
Conclusion
The findings of this study suggested that the prevalence of behavioral addiction among school adolescents has been relatively higher than that of previous studies, emphasizing the need for community-based prevention and intervention strategies tailored to the sex difference and psychological factors associated with adolescent behavioral addictions.
3.Prediction of Cancer Incidence and Mortality in Korea, 2025
Kyu-Won JUNG ; Mee Joo KANG ; Eun Hye PARK ; E Hwa YUN ; Hye-Jin KIM ; Jeong-Eun KIM ; Hyun-Joo KONG ; Kui Son CHOI ; Han-Kwang YANG
Cancer Research and Treatment 2025;57(2):331-338
Purpose:
This study aimed to project cancer incidence and mortality for 2025 to estimate Korea’s current cancer burden.
Materials and Methods:
Cancer incidence data from 1999 to 2022 were obtained from the Korea National Cancer Incidence Database, while cancer mortality data from 1993 to 2023 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and then by multiplying the projected age-specific rates by the anticipated age-specific population for 2025. A joinpoint regression model was applied to identify significant changes in trends, using only the most recent trend data for predictions.
Results:
A total of 304,754 new cancer cases and 84,019 cancer deaths are expected in Korea in 2025. The most commonly diagnosed cancer is projected to be thyroid cancer, followed by the colorectal, lung, breast, prostate and stomach cancers. These six cancers are expected to account for 63.8% of the total cancer burden. Lung cancer is expected to be the leading cause of cancer-related deaths, followed by liver, colorectal, pancreatic, stomach, and gallbladder cancers, together comprising 66.6% of total cancer deaths.
Conclusion
The increasing incidence of female breast cancer and the rise in prostate and pancreatic cancers are expected to continue. As aging accelerates, cancer commonly found in older adults are projected to rise significantly.
4.Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2022
Eun Hye PARK ; Kyu-Won JUNG ; Nam Ju PARK ; Mee Joo KANG ; E Hwa YUN ; Hye-Jin KIM ; Jeong-Eun KIM ; Hyun-Joo KONG ; Kui-Son CHOI ; Han-Kwang YANG ;
Cancer Research and Treatment 2025;57(2):312-330
Purpose:
The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2022, with international comparisons.
Materials and Methods:
Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2022), with survival follow-up until December 31, 2023. Mortality data obtained from Statistics Korea, while international comparisons were based on GLOBOCAN data.
Results:
In 2022, 282,047 newly diagnosed cancer cases (age-standardized rate [ASR], 287.0 per 100,000) and 83,378 deaths from cancer (ASR, 65.7 per 100,000) were reported. The proportion of localized-stage cancers increased from 45.6% in 2005 to 50.9% in 2022. Stomach, colorectal, and breast cancer showed increased localized-stage diagnoses by 18.1, 18.5, and 9.9 percentage points, respectively. Compared to 2001-2005, the 5-year relative survival (2018-2022) increased by 20.4 percentage points for stomach cancer, 7.6 for colorectal cancer, and 5.6 for breast cancer. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence (M/I) ratios for these cancers. The 5-year relative survival (2018-2022) was 72.9%, contributing to over 2.59 million prevalent cases in 2022.
Conclusion
Since the launch of the National Cancer Screening Program in 2002, early detection has improved, increasing the diagnosis of localized-stage cancers and survival rates. Korea recorded the lowest M/I ratio among major comparison countries, demonstrating the effectiveness of its National Cancer Control Program.
5.Prospective Evaluation of Accelerated Brain MRI Using Deep Learning-Based Reconstruction: Simultaneous Application to 2D Spin-Echo and 3D Gradient-Echo Sequences
Kyu Sung CHOI ; Chanrim PARK ; Ji Ye LEE ; Kyung Hoon LEE ; Young Hun JEON ; Inpyeong HWANG ; Roh Eul YOO ; Tae Jin YUN ; Mi Ji LEE ; Keun-Hwa JUNG ; Koung Mi KANG
Korean Journal of Radiology 2025;26(1):54-64
Objective:
To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials and Methods:
This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed.
Results:
Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29).
Conclusion
Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.
6.Prevalence and Factors Influencing Behavioral Addictions among School Adolescents: A Study in the Gwangju-Jeonnam Region
Narae KIM ; Bo-Hyun YOON ; Hyunju YUN ; Hyoung-Yeon KIM ; Ha-Ran JUNG ; Yuran JEONG ; Suhee PARK ; Young-Hwa SEA
Mood and Emotion 2025;23(1):11-20
Background:
The aim of this study is to evaluate the prevalence and associated psychosocial factors of behavioral addictions among school adolescents living in the Gwangju and Jeonnam regions in Korea.
Methods:
A self-reported survey was conducted from December 4, 2023, to January 31, 2024, including 855 middle and high school students residing in the Gwangju-Jeonnam regions. Aside from the information on demographic characteristics, data on depression, anxiety, Internet gaming addiction, gambling problems, and resilience was obtained.
Results:
The prevalence of Internet gaming addiction among adolescents was 5.4%, while the prevalence of gambling problems was 3.3%. The male adolescents had a significantly higher risk of behavioral addiction compared with the female adolescents. The logistic regression analysis revealed that male and depression were significant risk factors for Internet gaming addiction. For gambling problems, male was identified as a significant risk factor.
Conclusion
The findings of this study suggested that the prevalence of behavioral addiction among school adolescents has been relatively higher than that of previous studies, emphasizing the need for community-based prevention and intervention strategies tailored to the sex difference and psychological factors associated with adolescent behavioral addictions.
7.Prospective Evaluation of Accelerated Brain MRI Using Deep Learning-Based Reconstruction: Simultaneous Application to 2D Spin-Echo and 3D Gradient-Echo Sequences
Kyu Sung CHOI ; Chanrim PARK ; Ji Ye LEE ; Kyung Hoon LEE ; Young Hun JEON ; Inpyeong HWANG ; Roh Eul YOO ; Tae Jin YUN ; Mi Ji LEE ; Keun-Hwa JUNG ; Koung Mi KANG
Korean Journal of Radiology 2025;26(1):54-64
Objective:
To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials and Methods:
This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed.
Results:
Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29).
Conclusion
Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.
8.Prevalence and Factors Influencing Behavioral Addictions among School Adolescents: A Study in the Gwangju-Jeonnam Region
Narae KIM ; Bo-Hyun YOON ; Hyunju YUN ; Hyoung-Yeon KIM ; Ha-Ran JUNG ; Yuran JEONG ; Suhee PARK ; Young-Hwa SEA
Mood and Emotion 2025;23(1):11-20
Background:
The aim of this study is to evaluate the prevalence and associated psychosocial factors of behavioral addictions among school adolescents living in the Gwangju and Jeonnam regions in Korea.
Methods:
A self-reported survey was conducted from December 4, 2023, to January 31, 2024, including 855 middle and high school students residing in the Gwangju-Jeonnam regions. Aside from the information on demographic characteristics, data on depression, anxiety, Internet gaming addiction, gambling problems, and resilience was obtained.
Results:
The prevalence of Internet gaming addiction among adolescents was 5.4%, while the prevalence of gambling problems was 3.3%. The male adolescents had a significantly higher risk of behavioral addiction compared with the female adolescents. The logistic regression analysis revealed that male and depression were significant risk factors for Internet gaming addiction. For gambling problems, male was identified as a significant risk factor.
Conclusion
The findings of this study suggested that the prevalence of behavioral addiction among school adolescents has been relatively higher than that of previous studies, emphasizing the need for community-based prevention and intervention strategies tailored to the sex difference and psychological factors associated with adolescent behavioral addictions.
9.Prediction of Cancer Incidence and Mortality in Korea, 2025
Kyu-Won JUNG ; Mee Joo KANG ; Eun Hye PARK ; E Hwa YUN ; Hye-Jin KIM ; Jeong-Eun KIM ; Hyun-Joo KONG ; Kui Son CHOI ; Han-Kwang YANG
Cancer Research and Treatment 2025;57(2):331-338
Purpose:
This study aimed to project cancer incidence and mortality for 2025 to estimate Korea’s current cancer burden.
Materials and Methods:
Cancer incidence data from 1999 to 2022 were obtained from the Korea National Cancer Incidence Database, while cancer mortality data from 1993 to 2023 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and then by multiplying the projected age-specific rates by the anticipated age-specific population for 2025. A joinpoint regression model was applied to identify significant changes in trends, using only the most recent trend data for predictions.
Results:
A total of 304,754 new cancer cases and 84,019 cancer deaths are expected in Korea in 2025. The most commonly diagnosed cancer is projected to be thyroid cancer, followed by the colorectal, lung, breast, prostate and stomach cancers. These six cancers are expected to account for 63.8% of the total cancer burden. Lung cancer is expected to be the leading cause of cancer-related deaths, followed by liver, colorectal, pancreatic, stomach, and gallbladder cancers, together comprising 66.6% of total cancer deaths.
Conclusion
The increasing incidence of female breast cancer and the rise in prostate and pancreatic cancers are expected to continue. As aging accelerates, cancer commonly found in older adults are projected to rise significantly.
10.Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2022
Eun Hye PARK ; Kyu-Won JUNG ; Nam Ju PARK ; Mee Joo KANG ; E Hwa YUN ; Hye-Jin KIM ; Jeong-Eun KIM ; Hyun-Joo KONG ; Kui-Son CHOI ; Han-Kwang YANG ;
Cancer Research and Treatment 2025;57(2):312-330
Purpose:
The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2022, with international comparisons.
Materials and Methods:
Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2022), with survival follow-up until December 31, 2023. Mortality data obtained from Statistics Korea, while international comparisons were based on GLOBOCAN data.
Results:
In 2022, 282,047 newly diagnosed cancer cases (age-standardized rate [ASR], 287.0 per 100,000) and 83,378 deaths from cancer (ASR, 65.7 per 100,000) were reported. The proportion of localized-stage cancers increased from 45.6% in 2005 to 50.9% in 2022. Stomach, colorectal, and breast cancer showed increased localized-stage diagnoses by 18.1, 18.5, and 9.9 percentage points, respectively. Compared to 2001-2005, the 5-year relative survival (2018-2022) increased by 20.4 percentage points for stomach cancer, 7.6 for colorectal cancer, and 5.6 for breast cancer. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence (M/I) ratios for these cancers. The 5-year relative survival (2018-2022) was 72.9%, contributing to over 2.59 million prevalent cases in 2022.
Conclusion
Since the launch of the National Cancer Screening Program in 2002, early detection has improved, increasing the diagnosis of localized-stage cancers and survival rates. Korea recorded the lowest M/I ratio among major comparison countries, demonstrating the effectiveness of its National Cancer Control Program.

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