Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Objective: : Korea’s healthcare system and policy promotes early, actively stroke treatment to improve prognosis. This study represents stroke epidemiology and outcomes in Korea. Methods: : This study investigated data from the Acute Stroke Assessment Registry. The registry collects data from over 220 hospitals nationwide, focusing on quality stroke service management. Data analysis included patient demographics, stroke severity assessment, and discharge prognosis measurement using standardized scales. Results: : Eighty-six thousand five hundred sixty-eight acute stroke patients were collected with demographic and clinical characteristics during 18 months from 2016, 2018, and between 2020 to 2021, focusing on acute subarachnoid hemorrhage (SAH), acute intracerebral hemorrhage (ICH), and acute ischemic stroke. Of these 86568 patients, 8.3% was SAH, 16.3% ICH, and 74.9% ischemic stroke. Trends showed decreasing SAH and increasing ICH cases over the years. 68.3% stroke patients had the clear onset time. 49.6% stroke patients arrived within 4.5 hours of symptom onset, with more patients treated at general hospitals. Good functional outcomes at discharge was obtained with 58.3% of acute stroke patients, 55.9% of SAH patients, 34.6% of ICH patients, and 63.8% of ischemic stroke patients. Conclusion : The results showed that ischemic stroke was the most common subtype, followed by ICH and SAH. Prognosis differed among subtypes, with favorable outcomes more common in ischemic stroke and SAH compared to ICH.

Objective: : Korea’s healthcare system and policy promotes early, actively stroke treatment to improve prognosis. This study represents stroke epidemiology and outcomes in Korea. Methods: : This study investigated data from the Acute Stroke Assessment Registry. The registry collects data from over 220 hospitals nationwide, focusing on quality stroke service management. Data analysis included patient demographics, stroke severity assessment, and discharge prognosis measurement using standardized scales. Results: : Eighty-six thousand five hundred sixty-eight acute stroke patients were collected with demographic and clinical characteristics during 18 months from 2016, 2018, and between 2020 to 2021, focusing on acute subarachnoid hemorrhage (SAH), acute intracerebral hemorrhage (ICH), and acute ischemic stroke. Of these 86568 patients, 8.3% was SAH, 16.3% ICH, and 74.9% ischemic stroke. Trends showed decreasing SAH and increasing ICH cases over the years. 68.3% stroke patients had the clear onset time. 49.6% stroke patients arrived within 4.5 hours of symptom onset, with more patients treated at general hospitals. Good functional outcomes at discharge was obtained with 58.3% of acute stroke patients, 55.9% of SAH patients, 34.6% of ICH patients, and 63.8% of ischemic stroke patients. Conclusion : The results showed that ischemic stroke was the most common subtype, followed by ICH and SAH. Prognosis differed among subtypes, with favorable outcomes more common in ischemic stroke and SAH compared to ICH.

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.

Recent studies have shown an increased abundance of Sphingomonas paucimobilis, an aerobic, Gram-negative bacterium with a distinctive cell envelope rich in glycosphingolipids, within the gut microbiome of individuals with Alzheimer Disease (AD). However, the fact that S. paucimobilis is a well-known pathogen associated with nosocomial infections presents a significant challenge in investigating whether its presence in the gut microbiome is detrimental or beneficial, particularly in the context of AD. This study examines the impact of S. paucimobilis-derived extracellular vesicles (Spa-EV) on Aβ-induced pathology in cellular and animal models of AD. Microarray analysis reveals that Spa-EV treatment modulates Aβ42-induced alterations in gene expression in both HT22 neuronal cells and BV2 microglia cells. Among the genes significantly affected by SpaEV, notable examples include Bdnf, Nt3/4, and Trkb, which are key players of neurotrophic signaling; Pgc1α, an upstream regulator of mitochondrial biogenesis; Mecp2 and Sirt1, epigenetic factors that regulate numerous gene expressions; and Il1β, Tnfα, and Nfκb-p65, which are associated with neuroinflammation. Remarkably, Spa-EV effectively reverses Aβ42-induced alteration in the expression of these genes through the upregulation of Mecp2. Furthermore, administration of Spa-EV in Tg-APP/PS1 mice restores the reduced expression of neurotrophic factors, Pgc1α, MeCP2, and Sirt1, while suppressing the increased expression of proinflammatory genes in the brain. Our results indicate that Spa-EV has the potential to reverse Aβ-induced dysregulation of gene expression in neuronal and microglial cells. These alterations encompass those essential for neurotrophic signaling and neuronal plasticity, mitochondrial function, and the regulation of inflammatory processes.

Purpose: Potassium voltage-gated channel subfamily Q member 2 (KCNQ2)-related epilepsy, caused by mutations in the KCNQ2 gene, encompasses a spectrum of epileptic phenotypes, ranging from self-limited epilepsy to severe developmental and epileptic encephalopathy (DEE). Although the mutational background of these disorders has been characterized, predicting outcomes based solely on genetic variants remains challenging. Methods: This multicenter observational study investigated the clinical features, genotype-phenotype correlations, and comorbidities in pediatric patients with KCNQ2-related epilepsy in Korea. Conducted across three tertiary hospitals, the study enrolled 20 pediatric patients with genetically confirmed KCNQ2-related epilepsy. Data were collected from medical records, including demographic information, age at seizure onset, types of seizures, comorbidities, and treatment history. Results: Of the 20 patients enrolled, nine had self-limited epilepsy, while 11 had DEE. Missense mutations were more prevalent in the DEE group, whereas truncation mutations were associated with milder forms of epilepsy. Although 75% of cases achieved effective seizure control, 55% of patients exhibited comorbidities such as intellectual disability and neuropsychiatric disorders. Genotype-phenotype correlations revealed variability in clinical outcomes, with specific mutations in similar regions resulting in different phenotypes. Conclusion This study highlights the complexity of KCNQ2-related epilepsy, demonstrating that genotype-phenotype correlations are not straightforward and may be influenced by genetic modifiers, environmental factors, or dominant negative effects. While seizure control often improves, neurodevelopmental challenges may persist, underscoring the need for therapeutic approaches that address both seizure management and developmental support. Further research into the relevant non-genetic factors is essential to enhance the understanding and treatment of KCNQ2-related epilepsy.

Purpose: Potassium voltage-gated channel subfamily Q member 2 (KCNQ2)-related epilepsy, caused by mutations in the KCNQ2 gene, encompasses a spectrum of epileptic phenotypes, ranging from self-limited epilepsy to severe developmental and epileptic encephalopathy (DEE). Although the mutational background of these disorders has been characterized, predicting outcomes based solely on genetic variants remains challenging. Methods: This multicenter observational study investigated the clinical features, genotype-phenotype correlations, and comorbidities in pediatric patients with KCNQ2-related epilepsy in Korea. Conducted across three tertiary hospitals, the study enrolled 20 pediatric patients with genetically confirmed KCNQ2-related epilepsy. Data were collected from medical records, including demographic information, age at seizure onset, types of seizures, comorbidities, and treatment history. Results: Of the 20 patients enrolled, nine had self-limited epilepsy, while 11 had DEE. Missense mutations were more prevalent in the DEE group, whereas truncation mutations were associated with milder forms of epilepsy. Although 75% of cases achieved effective seizure control, 55% of patients exhibited comorbidities such as intellectual disability and neuropsychiatric disorders. Genotype-phenotype correlations revealed variability in clinical outcomes, with specific mutations in similar regions resulting in different phenotypes. Conclusion This study highlights the complexity of KCNQ2-related epilepsy, demonstrating that genotype-phenotype correlations are not straightforward and may be influenced by genetic modifiers, environmental factors, or dominant negative effects. While seizure control often improves, neurodevelopmental challenges may persist, underscoring the need for therapeutic approaches that address both seizure management and developmental support. Further research into the relevant non-genetic factors is essential to enhance the understanding and treatment of KCNQ2-related epilepsy.

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 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.

Recent studies have shown an increased abundance of Sphingomonas paucimobilis, an aerobic, Gram-negative bacterium with a distinctive cell envelope rich in glycosphingolipids, within the gut microbiome of individuals with Alzheimer Disease (AD). However, the fact that S. paucimobilis is a well-known pathogen associated with nosocomial infections presents a significant challenge in investigating whether its presence in the gut microbiome is detrimental or beneficial, particularly in the context of AD. This study examines the impact of S. paucimobilis-derived extracellular vesicles (Spa-EV) on Aβ-induced pathology in cellular and animal models of AD. Microarray analysis reveals that Spa-EV treatment modulates Aβ42-induced alterations in gene expression in both HT22 neuronal cells and BV2 microglia cells. Among the genes significantly affected by SpaEV, notable examples include Bdnf, Nt3/4, and Trkb, which are key players of neurotrophic signaling; Pgc1α, an upstream regulator of mitochondrial biogenesis; Mecp2 and Sirt1, epigenetic factors that regulate numerous gene expressions; and Il1β, Tnfα, and Nfκb-p65, which are associated with neuroinflammation. Remarkably, Spa-EV effectively reverses Aβ42-induced alteration in the expression of these genes through the upregulation of Mecp2. Furthermore, administration of Spa-EV in Tg-APP/PS1 mice restores the reduced expression of neurotrophic factors, Pgc1α, MeCP2, and Sirt1, while suppressing the increased expression of proinflammatory genes in the brain. Our results indicate that Spa-EV has the potential to reverse Aβ-induced dysregulation of gene expression in neuronal and microglial cells. These alterations encompass those essential for neurotrophic signaling and neuronal plasticity, mitochondrial function, and the regulation of inflammatory processes.