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: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background: Antithyroid drug (ATD) treatment is the preferred initial treatment for Graves’ disease (GD) in South Korea, despite higher treatment failure rates than radioactive iodine (RAI) therapy or thyroidectomy. This study aimed to evaluate the incidence of treatment failure associated with the primary modalities for GD treatment in real-world practice. Methods: We included 452,001 patients diagnosed with GD between 2004 and 2020 from the Korean National Health Insurance Service-National Health Information Database. Treatment failure was defined as switching from ATD, RAI, or thyroidectomy treatments, and for ATD specifically, inability to discontinue medication for over 2 years. Results: Mean age was 46.2 years, with females constituting 70.8%. Initial treatments for GD included ATDs (98.0%), thyroidectomy (1.3%), and RAI (0.7%), with a noted increment in ATD application from 96.2% in 2004 to 98.8% in 2020. During a median follow- up of 8.5 years, the treatment failure rates were 58.5% for ATDs, 21.3% for RAI, and 2.1% for thyroidectomy. Multivariate analysis indicated that the hazard ratio for treatment failure with ATD was 2.81 times higher than RAI. RAI treatments ≥10 mCi had 37% lower failure rates than doses <10 mCi. Conclusion ATDs are the most commonly used for GD in South Korea, followed by thyroidectomy and RAI. Although the risk of treatment failure for ATD is higher than that of RAI therapy, initial RAI treatment in South Korea is relatively limited compared to that in Western countries. Further studies are required to evaluate the cause of low initial RAI treatment rates in South Korea.

Purpose: While fluoropyrimidine-based chemotherapy regimens are recommended second-line treatment for patients with advanced biliary tract cancer (BTC), there have been no studies comparing different regimens head-to-head. Materials and Methods: We performed individual patient-level meta-analysis based on data from the intention-to-treat population of the phase 2b NIFTY trial (liposomal irinotecan [nal-IRI] plus fluorouracil and leucovorin [5-FU/LV] vs. 5-FU/LV; NCT03542508) and the phase 2 FIReFOX trial (modified oxaliplatin plus 5-FU/LV [mFOLFOX] vs. modified irinotecan plus 5-FU/LV [mFOLFIRI]; NCT03464968). Pairwise log-rank tests and multivariable analysis using Cox proportional hazards modeling with shared frailty to account for the trial's effect were used to compare overall survival (OS) between regimens. Results: A total of 277 patients were included. The nal-IRI plus 5-FU/LV group (n=88) showed significantly better OS compared to the mFOLFOX group (n=49, pairwise log-rank, p=0.02), and mFOLFIRI group (n=50, p=0.03). Multivariable analysis showed consistent trends in OS with adjusted hazard ratios of 1.39 (mFOLFOX vs. nal-IRI plus 5-FU/LV: 95% confidence interval [CI], 0.93 to 2.07; p=0.11) and 1.36 (mFOLFIRI vs. nal-IRI plus 5-FU/LV: 95% CI, 0.92 to 2.03; p=0.13), respectively. Compared to the 5-FU/LV group, the mFOLFOX group and the mFOLFIRI group did not show differences in terms of OS (pairwise log-rank p=0.83 and p=0.58, respectively). The nal-IRI plus 5-FU/LV group experienced more frequent diarrhea, while the mFOLFOX group experienced peripheral neuropathy. Conclusion Nal-IRI plus 5-FU/LV showed favorable survival outcomes compared to mFOLFOX, mFOLFIRI, or 5-FU/LV. The safety profiles of these regimens should be considered along with efficacy.

Purpose: Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups. Materials and Methods: A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease. Results: Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment. Conclusion HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.

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: The diagnosis of tuberculous pleural effusion (TPE) often relies on pleural fluid adenosine deaminase (ADA) levels. The diagnostic utility of ADA, however, is influenced by the prevalence of tuberculosis (TB) in local populations. Malignant pleural effusion (MPE) cases can exhibit moderately elevated ADA levels comparable to those seen in TPE. As population aging potentially impacts ADA levels, global TB incidence is decreasing whereas the burden of malignancy is on the rise. Consequently, epidemiological shifts and temporal changes in ADA distribution complicate the differential diagnosis between TPE and MPE when ADA levels are within the 40–70 IU/L range. Nonetheless, data specific to this subset are scarce. Methods: This retrospective study included consecutive patients aged > 18 years with confirmed TPE and MPE, spanning from 2012 to 2023. ADA levels in pleural fluid were categorized into three groups: < 40 IU/L, 40–70 IU/L, and > 70 IU/L. The study examined annual trends in the frequency of new cases and ADA level distributions over time and identified discriminating factors between TPE and MPE in cases with ADA levels of 40–70 IU/L. Results: In total, 297 TPE and 369 MPE cases were included in this study. Over the study period, the frequency of TPE progressively declined, while that of MPE increased. In the most recent four-year period, new TPE and MPE cases with ADA levels of 40–70 IU/L occurred at comparable numbers. Multivariable analysis identified pleural fluid carcinoembryonic antigen (CEA) levels and the number of focal pleural nodules as independent predictors for MPE. Specifically, the presence of either CEA levels > 15.7 ng/mL or more than eight pleural nodules yielded the highest diagnostic accuracy with a sensitivity of 88%, specificity of 100%, and an area under the curve of 0.95. Conclusion The differential diagnosis between TPE and MPE with pleural ADA levels of 40–70 IU/L has become increasingly critical due to evolving epidemiological patterns and ADA distribution changes over time. Pleural fluid CEA levels and the characteristics of pleural nodules may offer valuable guidance in distinguishing between TPE and MPE within this diagnostic gray zone.

Background: The diagnosis of tuberculous pleural effusion (TPE) often relies on pleural fluid adenosine deaminase (ADA) levels. The diagnostic utility of ADA, however, is influenced by the prevalence of tuberculosis (TB) in local populations. Malignant pleural effusion (MPE) cases can exhibit moderately elevated ADA levels comparable to those seen in TPE. As population aging potentially impacts ADA levels, global TB incidence is decreasing whereas the burden of malignancy is on the rise. Consequently, epidemiological shifts and temporal changes in ADA distribution complicate the differential diagnosis between TPE and MPE when ADA levels are within the 40–70 IU/L range. Nonetheless, data specific to this subset are scarce. Methods: This retrospective study included consecutive patients aged > 18 years with confirmed TPE and MPE, spanning from 2012 to 2023. ADA levels in pleural fluid were categorized into three groups: < 40 IU/L, 40–70 IU/L, and > 70 IU/L. The study examined annual trends in the frequency of new cases and ADA level distributions over time and identified discriminating factors between TPE and MPE in cases with ADA levels of 40–70 IU/L. Results: In total, 297 TPE and 369 MPE cases were included in this study. Over the study period, the frequency of TPE progressively declined, while that of MPE increased. In the most recent four-year period, new TPE and MPE cases with ADA levels of 40–70 IU/L occurred at comparable numbers. Multivariable analysis identified pleural fluid carcinoembryonic antigen (CEA) levels and the number of focal pleural nodules as independent predictors for MPE. Specifically, the presence of either CEA levels > 15.7 ng/mL or more than eight pleural nodules yielded the highest diagnostic accuracy with a sensitivity of 88%, specificity of 100%, and an area under the curve of 0.95. Conclusion The differential diagnosis between TPE and MPE with pleural ADA levels of 40–70 IU/L has become increasingly critical due to evolving epidemiological patterns and ADA distribution changes over time. Pleural fluid CEA levels and the characteristics of pleural nodules may offer valuable guidance in distinguishing between TPE and MPE within this diagnostic gray zone.