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.

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.

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.

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.

Purpose: To confirm the clinical features of hemicentral retinal vein occlusion and identify predictors of visual outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with hemicentral retinal vein occlusion between January 2018 and December 2022 and followed for more than 6 months. Patients underwent intravitreal injections as necessary for intraretinal edema. Visual acuity, central macular thickness, ellipsoid zone damage, and the location of inner retinal layer edema were assessed. Patients were categorized into groups A and group B based on the visual acuity at 6 months. Results: In total, 20 eyes were followed, with 15 eyes observed for up to 12 months. Seven patients (35.0%) had diabetes and 11 (55.0%) had hypertension. There was a correlation between poor vision at 6 months and hypertension (p = 0.033). The visual acuity of all patients improved from a logMAR of 0.96 at the initial visit to a logMAR of 0.35 at 6 months (p = 0.005). In the group with good initial visual acuity, there were no significant changes in visual acuity during the follow-up period (p = 0.444). The group with good visual acuity at 6 months had a lower degree of photoreceptor ellipsoid zone disruption compared to the group with poor initial vision, indicating a normal structure (p = 0.015). Conclusions During follow-up of patients with hemicentral retinal vein occlusion, overall visual acuity improved over time. Patients with good initial acuity maintained it. Favorable visual outcomes can be expected if the ellipsoid zone has a normal structure at the time of the first examination.