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PurposeThis study aims to investigate the interobserver variability in the quantitative assessment of liver fat content using ultrasound attenuation imaging technology (USAT).MethodsThis prospective, single‐center study included 96 adult patients who were either diagnosed with or suspected of having metabolic dysfunction‐associated steatotic liver disease. Independent observers, blinded to each other's assessments, evaluated hepatic steatosis visually and through USAT measurements. Separate measurements were taken at five intercostal and subcostal sites, and the median values of these measurements were recorded. The correlation between USAT measurements and visual steatosis grades was examined using Spearman's correlation test. Intraclass correlation coefficient (ICC) and Bland–Altman analysis were used to evaluate the interobserver variability of USAT measurements.ResultsInterobserver agreement for USAT measurements was excellent for the intercostal examination and good for the subcostal examination (p < 0.001). Body mass index did not significantly affect the level of interobserver agreement. Interobserver variability in Bland–Altman plots of USAT measurements was within the 95% limits of agreement. USAT measurements correlated very strongly with the visual degree of hepatic steatosis, both intercostal and subcostal (p < 0.001). USAT measurements were also significantly different between different visual degrees of hepatic steatosis (p < 0.001).ConclusionIn the assessment of hepatic steatosis, USAT measurements obtained from the intercostal space showed excellent agreement in terms of interobserver reproducibility.
PurposeThis study aims to investigate the interobserver variability in the quantitative assessment of liver fat content using ultrasound attenuation imaging technology (USAT).MethodsThis prospective, single‐center study included 96 adult patients who were either diagnosed with or suspected of having metabolic dysfunction‐associated steatotic liver disease. Independent observers, blinded to each other's assessments, evaluated hepatic steatosis visually and through USAT measurements. Separate measurements were taken at five intercostal and subcostal sites, and the median values of these measurements were recorded. The correlation between USAT measurements and visual steatosis grades was examined using Spearman's correlation test. Intraclass correlation coefficient (ICC) and Bland–Altman analysis were used to evaluate the interobserver variability of USAT measurements.ResultsInterobserver agreement for USAT measurements was excellent for the intercostal examination and good for the subcostal examination (p < 0.001). Body mass index did not significantly affect the level of interobserver agreement. Interobserver variability in Bland–Altman plots of USAT measurements was within the 95% limits of agreement. USAT measurements correlated very strongly with the visual degree of hepatic steatosis, both intercostal and subcostal (p < 0.001). USAT measurements were also significantly different between different visual degrees of hepatic steatosis (p < 0.001).ConclusionIn the assessment of hepatic steatosis, USAT measurements obtained from the intercostal space showed excellent agreement in terms of interobserver reproducibility.
Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) represents the most prevalent form of chronic liver disease and can progress to cirrhosis and hepatocellular carcinoma (HCC). While systemic inflammatory biomarkers have been linked to various liver diseases, their roles in MASLD remain uncertain. This cross-sectional study enrolled 6613 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) spanning from 2017 to March 2020. The study incorporated 10 inflammatory biomarkers, including ALI, SIRI, SII, SIPS, IBI, NLR, PLR, CAR, LMR, and PNI. Logistic regression, RCS regression, segmented regression, and subgroup analyses were implemented to explore the relationship between systemic inflammatory biomarkers and MASLD. After adjusting for vital confounders, half of the examined markers exhibited a significant association with MASLD, especially ALI, IBI, PLR, and CAR (P < 0.001). Most of these systemic inflammatory biomarkers, including ALI, SIRI, IBI, CAR, LMR, and PNI, demonstrated an obvious non-linear correlation with MASLD (P < 0.05). Moreover, the majority of these markers (SIRI, SII, IBI, NLR, PLR, and PNI) displayed notable variations in their associations with MASLD among various BMI categories (P < 0.05). In conclusion, systemic inflammatory biomarkers demonstrated a significant association with MASLD risk. Further large-scale prospective studies may be warranted to validate this relationship.
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