Background: This study aimed to identify the clinical characteristics of multidrug-resistant/ rifampicin-resistant tuberculosis (MDR/RR-TB) in the Republic of Korea. Methods: Data of notified people with tuberculosis between July 2018 and December 2021 were retrieved from the Korea Tuberculosis Cohort database. MDR/RR-TB was further categorized according to isoniazid susceptibility as follows: multidrug-resistant tuberculosis (MDR-TB), rifampicin-monoresistant tuberculosis (RMR-TB), and RR-TB if susceptibility to isoniazid was unknown. Multivariable logistic regression analysis was conducted to identify the factors associated with MDR/RR-TB. Results: Between 2018 and 2021, the proportion of MDR/RR-TB cases among all TB cases and TB cases with known drug susceptibility test results was 2.1% (502/24,447). The proportions of MDR/RR-TB and MDR-TB cases among TB cases with known drug susceptibility test results were 3.3% (502/15,071) and 1.9% (292/15,071), respectively. Among all cases of rifampicin resistance, 31.7% (159/502) were RMR-TB and 10.2% (51/502) were RR-TB. Multivariable logistic regression analyses revealed that younger age, foreigners, and prior tuberculosis history were significantly associated with MDR/ RR-TB. Conclusion Rapid identification of rifampicin resistance targeting the high-risk populations, such as younger generations, foreign-born individuals, and previously treated patients are necessary for patient-centered care.

Background: and Purpose: Brain atrophy, characterized by sulcal widening and ventricular enlargement, is a hallmark of neurodegenerative diseases such as Alzheimer’s disease. Visual assessments are subjective and variable, while automated methods struggle with subtle intensity differences and standardization, highlighting limitations in both approaches. This study aimed to develop and evaluate a novel method focusing on cerebrospinal fluid (CSF) regions by assessing segmentation accuracy, detecting stage-specific atrophy patterns, and testing generalizability to unstandardized datasets. Methods: We utilized T1-weighted magnetic resonance imaging data from 3,315 participants from Samsung Medical Center and 1,439 participants from other hospitals. Segmentation accuracy was evaluated using the Dice similarity coefficient (DSC), and W-scores were calculated for each region of interest (ROI) to assess stage-specific atrophy patterns. Results: The segmentation demonstrated high accuracy, with average DSC values exceeding 0.9 for ventricular and hippocampal regions and above 0.8 for cortical regions. Significant differences in W-scores were observed across cognitive stages (cognitively unimpaired, mild cognitive impairment, dementia of Alzheimer’s type) for all ROIs (all, p<0.05). Similar trends were observed in the images from other hospitals, confirming the algorithm’s generalizability to datasets without prior standardization. Conclusions This study demonstrates the robustness and clinical applicability of a novel CSF-focused segmentation method for assessing brain atrophy. The method provides a scalable and objective framework for evaluating structural changes across cognitive stages and holds potential for broader application in neurodegenerative disease research and clinical practice.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Purpose: Pancreatic cancer has a poor prognosis; however, the implementation of neoadjuvant treatment enables borderline resectable cases to undergo curative resection and improves the overall survival rate. Attempts have been made to expand the eligibility criteria for neoadjuvant treatment, even in resectable cases. Some studies have suggested a correlation between vein abutment and poor prognosis or that the abutment angle may affect prognosis. This study investigated the anatomical factors affecting the vessel abutment angle and its prognostic value in pancreatic cancer. Methods: Patients with pancreatic ductal adenocarcinoma who underwent surgery between 2012 and 2017 were included in this study. Patients who underwent neoadjuvant treatment were excluded. Data from only the intent-to-treat pancreaticoduodenectomy group were included in the analysis. Clinicopathological characteristics; preoperative factors such as CA 19-9, preoperative biliary drainage, American Society of Anesthesiologists physical status classification, portal vein/superior mesenteric vein contact angle measured via CT scan; and intraoperative factors were collected for analysis. Results: A total of 365 patients were included in this study, and the abutment group included 92 patients (25.2%). The abutment and no-contact groups did not show any significant differences in terms of the overall survival or diseasefree survival rate. Among the abutment groups, patients with less than 90° and 90°–180° did not show any significant differences. In the multivariate analysis, the only preoperative factor that had a prognostic effect was CA 19-9, a biological factor. Conclusion When there is no vessel invasion in the abutment group, upfront surgery should be considered because the angle does not affect the overall prognosis.

Background: This study aimed to identify the clinical characteristics of multidrug-resistant/ rifampicin-resistant tuberculosis (MDR/RR-TB) in the Republic of Korea. Methods: Data of notified people with tuberculosis between July 2018 and December 2021 were retrieved from the Korea Tuberculosis Cohort database. MDR/RR-TB was further categorized according to isoniazid susceptibility as follows: multidrug-resistant tuberculosis (MDR-TB), rifampicin-monoresistant tuberculosis (RMR-TB), and RR-TB if susceptibility to isoniazid was unknown. Multivariable logistic regression analysis was conducted to identify the factors associated with MDR/RR-TB. Results: Between 2018 and 2021, the proportion of MDR/RR-TB cases among all TB cases and TB cases with known drug susceptibility test results was 2.1% (502/24,447). The proportions of MDR/RR-TB and MDR-TB cases among TB cases with known drug susceptibility test results were 3.3% (502/15,071) and 1.9% (292/15,071), respectively. Among all cases of rifampicin resistance, 31.7% (159/502) were RMR-TB and 10.2% (51/502) were RR-TB. Multivariable logistic regression analyses revealed that younger age, foreigners, and prior tuberculosis history were significantly associated with MDR/ RR-TB. Conclusion Rapid identification of rifampicin resistance targeting the high-risk populations, such as younger generations, foreign-born individuals, and previously treated patients are necessary for patient-centered care.

Background: This study aimed to identify the clinical characteristics of multidrug-resistant/ rifampicin-resistant tuberculosis (MDR/RR-TB) in the Republic of Korea. Methods: Data of notified people with tuberculosis between July 2018 and December 2021 were retrieved from the Korea Tuberculosis Cohort database. MDR/RR-TB was further categorized according to isoniazid susceptibility as follows: multidrug-resistant tuberculosis (MDR-TB), rifampicin-monoresistant tuberculosis (RMR-TB), and RR-TB if susceptibility to isoniazid was unknown. Multivariable logistic regression analysis was conducted to identify the factors associated with MDR/RR-TB. Results: Between 2018 and 2021, the proportion of MDR/RR-TB cases among all TB cases and TB cases with known drug susceptibility test results was 2.1% (502/24,447). The proportions of MDR/RR-TB and MDR-TB cases among TB cases with known drug susceptibility test results were 3.3% (502/15,071) and 1.9% (292/15,071), respectively. Among all cases of rifampicin resistance, 31.7% (159/502) were RMR-TB and 10.2% (51/502) were RR-TB. Multivariable logistic regression analyses revealed that younger age, foreigners, and prior tuberculosis history were significantly associated with MDR/ RR-TB. Conclusion Rapid identification of rifampicin resistance targeting the high-risk populations, such as younger generations, foreign-born individuals, and previously treated patients are necessary for patient-centered care.

Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.