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.

Objective: Suicide is a complex issue influenced by various factors, including mental illness, economic, and cultural elements. Mental and behavioral disorders are significant contributors to suicide risk, and individuals who attempt self-harm often present with comorbidities. This study aims to identify the significance of characteristics and comorbidities among hospitalized patients who engaged in self-harm and have been diagnosed with mental and behavioral disorders. Methods: We targeted patients aged 19 or older who attempted self-harm and were hospitalized from the 2022 Korea National Hospital Discharge In-depth Injury Survey covering the period from 2008 to 2021. After applying sampling weights, the estimated total sample size was 10,140. The analysis was conducted using a general linear model for complex samples, incorporating analysis of variance and regression analyses. Additionally, network analysis was used to explore relationships among comorbidities. Results: The incidence of self-harm varied seasonally, peaking in spring, with higher rates observed in winter. Hospitalization duration was significantly longer when surgical interventions were required or when comorbidities were present. The average length of hospitalization was 20.52 days, but patients with alcohol-related addictions had a significantly longer stay (71.57 days). For each additional comorbidity, the hospitalization duration increased by 1.889 days. About 46.78% of patients had one or more comorbidities, with strong associations between mental disorders (F00–F99) and cases of poisoning or external injuries (S00–T98). Conclusion This study underscores the importance of managing comorbidities in patients with mental illness to reduce the clinical and social costs of self-harm.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Purpose: Recent development in perioperative treatment of resectable non–small cell lung cancer (NSCLC) have changed the landscape of early lung cancer management. The ADAURA trial has demonstrated the efficacy of adjuvant osimertinib treatment in resectable NSCLC patients; however, studies are required to show which subgroup of patients are at a high risk of relapse and require adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor treatment. This study evaluated risk factors for postoperative relapse among patients who underwent complete resection. Materials and Methods: Data were obtained from the Korean Association for Lung Cancer Registry (KALC-R), a database created using a retrospective sampling survey by the Korean Central Cancer Registry (KCCR) and the Lung Cancer Registration Committee. Results: A total of 3,176 patients who underwent curative resection was evaluated. The mean observation time was approximately 35.4 months. Among stage I to IIIA NSCLC patients, the EGFR-mutant subgroup included 867 patients, and 75.2%, 11.2%, and 11.8% were classified as stage I, stage II, and stage III, respectively. Within the EGFR-mutant subgroup, 44 (5.1%) and 121 (14.0%) patients showed early and late recurrence, respectively. Multivariate analysis on association with postoperative relapse among the EGFR-mutant subgroup showed that age, pathologic N and TNM stages, pleural invasion status, and surgery type were independent significant factors. Conclusion Among the population that underwent complete resection for early NSCLC with EGFR mutation, patients with advanced stage, pleural invasion, or limited resection are more likely to show postoperative relapse.

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.

Objective: Suicide is a complex issue influenced by various factors, including mental illness, economic, and cultural elements. Mental and behavioral disorders are significant contributors to suicide risk, and individuals who attempt self-harm often present with comorbidities. This study aims to identify the significance of characteristics and comorbidities among hospitalized patients who engaged in self-harm and have been diagnosed with mental and behavioral disorders. Methods: We targeted patients aged 19 or older who attempted self-harm and were hospitalized from the 2022 Korea National Hospital Discharge In-depth Injury Survey covering the period from 2008 to 2021. After applying sampling weights, the estimated total sample size was 10,140. The analysis was conducted using a general linear model for complex samples, incorporating analysis of variance and regression analyses. Additionally, network analysis was used to explore relationships among comorbidities. Results: The incidence of self-harm varied seasonally, peaking in spring, with higher rates observed in winter. Hospitalization duration was significantly longer when surgical interventions were required or when comorbidities were present. The average length of hospitalization was 20.52 days, but patients with alcohol-related addictions had a significantly longer stay (71.57 days). For each additional comorbidity, the hospitalization duration increased by 1.889 days. About 46.78% of patients had one or more comorbidities, with strong associations between mental disorders (F00–F99) and cases of poisoning or external injuries (S00–T98). Conclusion This study underscores the importance of managing comorbidities in patients with mental illness to reduce the clinical and social costs of self-harm.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

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.