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: To compare visual outcomes over 6 months between intravitreal anti-vascular endothelial growth factor (VEGF) therapy with or without pneumatic displacement in patients who were diagnosed with submacular hemorrhage secondary to polypoidal choroidal vasculopathy (PCV). Methods: This retrospective observational study included 12 eyes that underwent pneumatic displacement followed by anti-VEGF therapy (combined treatment group) and 17 eyes that underwent anti-VEGF monotherapy (anti-VEGF monotherapy group) for submacular hemorrhage secondary to PCV and were followed for at least 6 months. The best-corrected visual acuity (BCVA) was measured at diagnosis and at 1, 3, and 6 months. The BCVA at 6 months and degree of BCVA improvement during the 6 months of follow-up were compared between the 2 groups. Results: In the combined treatment group, the mean (± standard deviation) logarithm of minimal angle of resolution BCVA values at the defined periods were 1.40 ± 0.54, 1.08 ± 0.63, 0.83 ± 0.57, and 0.79 ± 0.64, respectively. In the anti-VEGF monotherapy group, the mean BCVAs were 1.48 ± 0.47, 1.31 ± 0.48, 1.13 ± 0.52, and 1.04 ± 0.67, respectively. BCVA was significantly improved in both the combined treatment group (p = 0.012) and the monotherapy group (p = 0.026). Neither the BCVA at 6 months nor the degree of improvement in the BCVA was different between the 2 treatment groups (p = 0.269 and p = 0.300, respectively). Conclusions No notable difference in efficacy was observed between intravitreal anti-VEGF therapy with or without pneumatic displacement in treating submacular hemorrhage secondary to PCV.

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.

Background: A decline in masticatory function may indicate brain dysfunction related to dementia, but the relationship between masticatory function and dementia risk remains unclear. This study aimed to investigate whether masticatory function is associated with the risk of cognitive decline and dementia. Methods: Data were obtained from the nationwide prospective cohort study of randomly sampled community-dwelling Koreans aged ≥ 60 years. The 5,064 non-demented participants, whose number of chewing cycles per bite was assessed by clinical interview, were followed for 8 years with biennial assessments of cognitive performance and clinical diagnoses of all-cause dementia and Alzheimer’s disease (AD). Structural brain magnetic resonance imaging was collected from a subset of cohort participants and their spouses for imaging analyses. Results: Males who chewed ≥ 30 cycles/bite had faster decline in global cognition and memory function and were at higher risk for incident all-cause dementia (hazard ratio [HR], 2.91; 95% confidence interval [CI], 1.18–7.18) and AD (HR, 3.22; 95% CI, 1.14–9.11) compared to males with less than 10 cycles/bite. Additionally, increased chewing cycles in males were associated with reduced brain volume, particularly in regions involved in compensatory cognitive control of mastication. There was no significant association between chewing cycles and the risk of dementia or brain volume in females. Conclusion Older men who frequently chew their meals could be considered a notable population at risk for dementia who should be carefully assessed for their cognitive trajectories.

Objective: To investigate the relationship between reduced glutathione (GSH), a key molecule of the antioxidant defense system in the blood, and glutathione reductase (GR), which reduces oxidized glutathione (glutathione disulfide [GSSG]) to GSH and maintains the redox balance, with the prevalence of Alzheimer’s dementia and cognitive decline. Methods: In all, 20 participants with Alzheimer’s dementia who completed the third follow-up clinical evaluation over 6 years were selected, and 20 participants with normal cognition were selected after age and sex matching. The GSH and GR concentrations were the independent variables. Clinical diagnosis and neurocognitive test scores were the dependent variables indicating cognitive status. Results: The higher the level of GR, the greater the possibility of having normal cognition than of developing Alzheimer’s dementia. Additionally, the higher the level of GR, the higher the neurocognitive test scores. However, this association was not significant for GSH. After 6 years, the conversion rate from normal cognition to cognitive impairment was significantly higher in the lower 50th percentile of the GR group than in the upper 50th percentile. Conclusion The higher the GR, the lower the prevalence of Alzheimer’s dementia and incidence of cognitive impairment and the higher the cognitive test scores. Therefore, GR is a potential protective biomarker against Alzheimer’s dementia and cognitive decline.

Background: Factors related to the development and severity of polycystic liver disease (PLD) have not been well established. We aimed to evaluate the genetic and epidemiologic risk factors of PLD in patients with autosomal dominant polycystic kidney disease (ADPKD). Methods: Adult patients with inherited cystic kidney disease were enrolled from May 2019 to May 2021. Demographic, clinical, and laboratory data were collected at the initial study visit. The severity of PLD was graded based on the height-adjusted total liver volume: < 1,000 mL/m (Gr1), 1,000–1,800 mL/m (Gr2), and > 1,800 mL/m (Gr3). Targeted exome sequencing was done by a gene panel including 89 ciliopathy-related genes. We searched out the relative factors to the presence and the severity of PLD using logistic regression analysis. Results: Of 602 patients with typical ADPKD, 461 (76.6%) patients had PLD. The patients with PLD showed female predominance and a higher frequency of other ADPKD-related complications. The genetic variants with truncating mutation of PKD1 (PKD1-proteintruncating [PT]) or PKD2 commonly affected the development and severity of PLD. An older age, female sex, and higher kidney volume with Mayo classification 1C-1E was significantly associated with the development of PLD, but not with the severity of PLD. On the other hand, higher body mass index, lower hemoglobin, and higher alkaline phosphatase (ALP) were the significant risk factors of severe PLD (≥ Gr2). Conclusion Hepatic involvement in ADPKD could be related to kidney manifestations and genetic variants including PKD1-PT or PKD2. Monitoring hemoglobin and ALP and evaluating the genetic variants might help predict severe PLD.