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: 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.

BACKGROUND: Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture. METHODS: This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts. RESULTS: Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring. CONCLUSION Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.

Purpose: Emphysematous pyelonephritis (EPN) is a life-threatening disease requiring immediate treatment. This multicenter retrospective cohort study aimed to analyze the mortality rate and risk factors associated with EPN. Materials and Methods: Between January 2011 and February 2021, 217 patients diagnosed with EPN via computed tomography who visited 14 teaching hospitals were retrospectively analyzed. Clinical data, including age, sex, comorbidities, Huang and Tseng classification, hydronephrosis, acute kidney injury, blood and urine tests, surgical interventions, percutaneous drainage, and conservative treatments, were compared between the survival and death groups. Risk factors for mortality due to EPN were analyzed using univariate and multivariate methods. Results: The mean age of survivors and deceased patients was 67.8 and 69.0 years, respectively (p=0.136). The sex distribution (male/female) was 48/146 and 8/15, respectively (p=0.298). Of the 217 patients, 23 died, resulting in a mortality rate of 10.6%. In univariate analysis, the Huang and Tseng classification (p=0.004), platelet count (p=0.005), and acute kidney injury (p=0.007) were significantly associated with mortality from EPN. In multivariate analysis, only the Huang and Tseng classification (p=0.029) was identified as a risk factor. Mortality rates according to the Huang and Tseng classification were as follows: class I (5.88%), class II (7.50%), class IIIa (14.28%), class IIIb (25.00%), and class IV (23.07%). Conclusions EPN is associated with a high mortality rate. Among various clinical factors, the Huang and Tseng classification was the most significant indicator for predicting mortality.

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.

BACKGROUND: Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture. METHODS: This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts. RESULTS: Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring. CONCLUSION Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.

Purpose: Emphysematous pyelonephritis (EPN) is a life-threatening disease requiring immediate treatment. This multicenter retrospective cohort study aimed to analyze the mortality rate and risk factors associated with EPN. Materials and Methods: Between January 2011 and February 2021, 217 patients diagnosed with EPN via computed tomography who visited 14 teaching hospitals were retrospectively analyzed. Clinical data, including age, sex, comorbidities, Huang and Tseng classification, hydronephrosis, acute kidney injury, blood and urine tests, surgical interventions, percutaneous drainage, and conservative treatments, were compared between the survival and death groups. Risk factors for mortality due to EPN were analyzed using univariate and multivariate methods. Results: The mean age of survivors and deceased patients was 67.8 and 69.0 years, respectively (p=0.136). The sex distribution (male/female) was 48/146 and 8/15, respectively (p=0.298). Of the 217 patients, 23 died, resulting in a mortality rate of 10.6%. In univariate analysis, the Huang and Tseng classification (p=0.004), platelet count (p=0.005), and acute kidney injury (p=0.007) were significantly associated with mortality from EPN. In multivariate analysis, only the Huang and Tseng classification (p=0.029) was identified as a risk factor. Mortality rates according to the Huang and Tseng classification were as follows: class I (5.88%), class II (7.50%), class IIIa (14.28%), class IIIb (25.00%), and class IV (23.07%). Conclusions EPN is associated with a high mortality rate. Among various clinical factors, the Huang and Tseng classification was the most significant indicator for predicting mortality.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

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.

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.