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: This study aimed to characterize the clinical patterns and severity of brain injury in neonates who survived extracorporeal membrane oxygenation (ECMO) therapy for acute respiratory failure during the neonatal period, to evaluate their short-term neurodevelopmental outcomes, and to identify the factors associated with these outcomes. Methods: We retrospectively reviewed the medical records of neonates who survived ECMO between 2018 and 2024. Based on brain magnetic resonance imaging (MRI) findings, the patients were classified into two groups: no/mild and moderate/severe brain injury. Neurodevelopmental outcomes were assessed at 12–40 months of age using the Bayley Scale of Infant Development II/III and/or the Korean Developmental Screening Test. Results: Among the 19 neonates included in the study, 18 (94.7%) showed varying degrees of brain injury on MRI (mild: 12, moderate: 1, severe: 5). Neonates with moderate/severe brain injury had significantly longer durations of ECMO support and extended durations of mechanical ventilation and were more likely to receive continuous renal replacement therapy than those with no or mild injury. Developmental delay was identified in 36.8% of survivors and was significantly associated with prolonged mechanical ventilation, longer neonatal intensive care unit stays, and a higher incidence of seizures. Conclusion Brain injury is frequently observed on MRI in neonates treated with ECMO. However, its direct association with adverse neurodevelopmental outcomes is not definitive. Since MRI findings alone cannot predict developmental outcomes, clinical and environmental factors should be integrated into prognostic assessments.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

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: This study aimed to characterize the clinical patterns and severity of brain injury in neonates who survived extracorporeal membrane oxygenation (ECMO) therapy for acute respiratory failure during the neonatal period, to evaluate their short-term neurodevelopmental outcomes, and to identify the factors associated with these outcomes. Methods: We retrospectively reviewed the medical records of neonates who survived ECMO between 2018 and 2024. Based on brain magnetic resonance imaging (MRI) findings, the patients were classified into two groups: no/mild and moderate/severe brain injury. Neurodevelopmental outcomes were assessed at 12–40 months of age using the Bayley Scale of Infant Development II/III and/or the Korean Developmental Screening Test. Results: Among the 19 neonates included in the study, 18 (94.7%) showed varying degrees of brain injury on MRI (mild: 12, moderate: 1, severe: 5). Neonates with moderate/severe brain injury had significantly longer durations of ECMO support and extended durations of mechanical ventilation and were more likely to receive continuous renal replacement therapy than those with no or mild injury. Developmental delay was identified in 36.8% of survivors and was significantly associated with prolonged mechanical ventilation, longer neonatal intensive care unit stays, and a higher incidence of seizures. Conclusion Brain injury is frequently observed on MRI in neonates treated with ECMO. However, its direct association with adverse neurodevelopmental outcomes is not definitive. Since MRI findings alone cannot predict developmental outcomes, clinical and environmental factors should be integrated into prognostic assessments.