Purpose: Adjuvant chemotherapy (AC) is recommended for muscle-invasive or lymph node-positive upper urinary tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). However, disease recurrences are frequently observed in pT1 disease, and AC may increase the risk of overtreatment in pT2 UTUC patients. This study aimed to validate a risk-adapted scoring model for selecting UTUC patients with ≤pT2 disease who would benefit from AC. Materials and Methods: We retrospectively analyzed 443 ≤pT2 UTUC patients who underwent RNU. A risk-adapted scoring model was applied, categorizing patients into low- or high-risk groups. Recurrence-free survival (RFS) and cancer-specific survival (CSS) were analyzed according to risk group. Results: Overall, 355 patients (80.1%) and 88 patients (19.9%) were categorized into the low- and high-risk groups, respectively, with the latter having higher pathological stages, concurrent carcinoma in situ, and synchronous bladder tumors. Disease recurrence occurred in 45 patients (10.2%), among whom 19 (5.4%) and 26 (29.5%) belonged to the low- and high-risk groups, respectively (p<0.001). High-risk patients had significantly shorter RFS (64.3% vs. 93.6% at 60 months; hazard ratio [HR] 13.66; p<0.001) and worse CSS (80.7% vs. 91.5% at 60 months; HR 4.25; p=0.002). Multivariate analysis confirmed that pT2 stage and the high-risk group were independent predictors of recurrence and cancer-specific death (p<0.001). Decision curve analysis for RFS showed larger net benefits with our model than with the T stage model. Conclusions The risk-adapted scoring model effectively predicts recurrence and identifies optimal candidates for AC post RNU in non-metastatic UTUC.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Cardio-oncology is a critical field due to the escalating significance of cardiovascular toxicity as a side effect of anti‑ cancer treatments. Cancer therapy-related cardiac dysfunction (CTRCD) is a prevalent condition associated with car‑ diovascular toxicity, necessitating effective strategies for prediction, monitoring, management, and tracking. This comprehensive review examines the definition and risk stratification of CTRCD, explores monitoring approaches during anticancer therapy, and highlights specific cardiovascular toxicities linked to various cancer treatments. These include anthracyclines, HER2-targeted agents, vascular endothelial growth factor inhibitors, immune checkpoint inhibitors, chimeric antigen receptor T-cell therapies, and tumor-infiltrating lymphocytes therapies. Incorporating the Korean data, this review offers insights into the regional nuances in managing CTRCD. Using systematic follow-up incorporating cardiovascular imaging and biomarkers, a better understanding and management of CTRCD can be achieved, optimizing the cardiovascular health of both cancer patients and survivors.

Background and Objectives: Inherited arrhythmia (IA) is a more common cause of sudden cardiac death in Asian population, but little is known about the genetic background of Asian IA probands. We aimed to investigate the clinical characteristics and analyze the genetic underpinnings of IA in a Korean cohort. Methods: This study was conducted in a multicenter cohort of the Korean IA Registry from 2014 to 2017. Genetic testing was performed using a next-generation sequencing panel including 174 causative genes of cardiovascular disease. Results: Among the 265 IA probands, idiopathic ventricular fibrillation (IVF) and Brugada Syndrome (BrS) was the most prevalent diseases (96 and 95 cases respectively), followed by long QT syndrome (LQTS, n=54). Two-hundred-sixteen probands underwent genetic testing, and 69 probands (31.9%) were detected with genetic variant, with yield of pathogenic or likely pathogenic variant as 6.4%. Left ventricular ejection fraction was significantly lower in genotype positive probands (54.7±11.3 vs. 59.3±9.2%, p=0.005). IVF probands showed highest yield of positive genotype (54.0%), followed by LQTS (23.8%), and BrS (19.5%). Conclusions There were significant differences in clinical characteristics and genetic yields among BrS, LQTS, and IVF. Genetic testing did not provide better yield for BrS and LQTS. On the other hand, in IVF, genetic testing using multiple gene panel might enable the molecular diagnosis of concealed genotype, which may alter future clinical diagnosis and management strategies.

Background: Propofol-based total intravenous anesthesia (TIVA) improves long-term outcomes after cancer surgery compared with inhalation anesthesia. However, its effect on patients undergoing non-small cell lung cancer (NSCLC) surgery remains unclear. We aimed to compare the oncological outcomes of TIVA and inhalation anesthesia after curative resection of early-stage NSCLC. Methods: We analyzed the medical records of patients diagnosed with stage I or II NSCLC who underwent curative resection at a tertiary university hospital between January 2010 and December 2017. The primary outcomes were recurrence-free survival (RFS) and overall survival (OS) according to anesthesia type. Results: We included 1,508 patients with stage I/II NSCLC. The patients were divided into the TIVA (n = 980) and Inhalation (n = 528) groups. The two groups were well-balanced in terms of baseline clinical characteristics. The TIVA group demonstrated significantly improved RFS (7.7 years, 95% CI [7.37, 8.02]) compared with the Inhalation group (6.8 years, 95% CI [6.30, 7.22], P = 0.003). Similarly, TIVA was superior to inhalation agents with respect to OS (median OS; 8.4 years, 95% CI [8.08, 8.69] vs. 7.3 years, 95% CI [6.81, 7.71]; P < 0.001). Multivariable Cox regression analysis revealed that TIVA was an independent prognostic factor related to recurrence (hazard ratio [HR]: 1.24, 95% CI [1.04, 1.47], P = 0.014) and OS (HR: 1.39, 95% CI [1.12, 1.72], P = 0.002). Conclusions Propofol-based TIVA was associated with better RFS and OS than inhalation anesthesia in patients with stage I/II NSCLC who underwent curative resection.