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 investigate the effects of postnatal systemic corticosteroids on neurodevelopment in very low birth weight (VLBW) preterm infants. Methods: This was a population-based study of the Korean Neonatal Network of VLBW infant born at 23+0 and 31+6 weeks of gestation between 2013 and 2020. VLBW preterm infants assessed using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III) at 18–24 months of corrected age and 3 years of age were enrolled. The primary outcomes were BSID-III scores and neurodevelopmental delays, with scores of <85. Socioeconomic status and clinical variables were adjusted for using multivariate regression analyses. Results: In total, 517 infants were enrolled in this study. Among the 216 (41.8%) infants who received postnatal systemic corticosteroids, the rate of cognitive delay was significantly higher at 18–24 months of corrected age than at 3 years of age. The rates of language and motor delays were significantly higher both at 18–24 months of corrected age and at 3 years of age. When multivariate logistic regression was performed, postnatal systemic corticosteroid use was significantly associated with cognitive delay at 18–24 months of corrected age, but not at 3 years of age. There was no significant association between postnatal systemic corticosteroid use and language or motor delay at 18-24 months of corrected age or at 3 years of age after multivariate logistic regression. Conclusion Postnatal systemic corticosteroid use in VLBW preterm infants increased the risk of cognitive delay at 18–24 months of corrected age, but not at 3 years.

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 investigate the effects of postnatal systemic corticosteroids on neurodevelopment in very low birth weight (VLBW) preterm infants. Methods: This was a population-based study of the Korean Neonatal Network of VLBW infant born at 23+0 and 31+6 weeks of gestation between 2013 and 2020. VLBW preterm infants assessed using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III) at 18–24 months of corrected age and 3 years of age were enrolled. The primary outcomes were BSID-III scores and neurodevelopmental delays, with scores of <85. Socioeconomic status and clinical variables were adjusted for using multivariate regression analyses. Results: In total, 517 infants were enrolled in this study. Among the 216 (41.8%) infants who received postnatal systemic corticosteroids, the rate of cognitive delay was significantly higher at 18–24 months of corrected age than at 3 years of age. The rates of language and motor delays were significantly higher both at 18–24 months of corrected age and at 3 years of age. When multivariate logistic regression was performed, postnatal systemic corticosteroid use was significantly associated with cognitive delay at 18–24 months of corrected age, but not at 3 years of age. There was no significant association between postnatal systemic corticosteroid use and language or motor delay at 18-24 months of corrected age or at 3 years of age after multivariate logistic regression. Conclusion Postnatal systemic corticosteroid use in VLBW preterm infants increased the risk of cognitive delay at 18–24 months of corrected age, but not at 3 years.

Microglial activation during aging is associated with neuroinflammation and cognitive impairment. Galectin-3 plays a crucial role in microglial activation and phagocytosis. However, the role of galectin-3 in the aged brain is not completely understood. In the present study, we investigated aging-related mechanisms and microglial galectin-3 expression in the mouse hippocampus using female 6-, 12-, and 24-month-old C57BL/6 mice. Western blot analysis revealed neurodegeneration, blood-brain barrier leakage, and increased levels of neuroinflammation-related proteins in 24-month-old mice compared to 6- and 12-month-old mice. Immunohistochemistry revealed an increase in activated microglia in the hippocampus of 24-month-old mice compared to 6- and 12-month-old mice. Furthermore, we found more galectin-3 and triggering receptor expressed on myeloid cells-2-positive microglia in 24-month-old mice compared to 6- and 12-month-old mice. Using primary mouse microglial cells, galectin -3 was also increased by lipopolysaccharide treatment. These findings suggest that galectin-3 may play an important role in microglial activation and neuroinflammation during brain aging.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.