Attenuation coefficient measurement in screening for metabolic dysfunctionassociated steatotic liver disease: between diagnostic accuracy and economic reality

Abstract

Purpose – to evaluate the diagnostic performance of ultrasound attenuation coefficient measurement (ACM) in detecting and grading hepatic steatosis and to assess its economic feasibility as a primary screening tool for metabolically associated steatotic liver disease (MASLD) in routine clinical practice. Materials and methods. The study included 168 adult patients aged 18–64 years who underwent comprehensive liver assessment under real-world clinical conditions. All participants received conventional B-mode ultrasound examination with attenuation coefficient measurement and hepatorenal index assessment, as well as magnetic resonance imaging with proton density fat fraction (MRI-PDFF). MRI-PDFF was used as the reference standard for the presence and severity of hepatic steatosis. Hepatic steatosis was defined using established MRI-PDFF thresholds, including binary classification (presence or absence of steatosis) and stratification by steatosis grade. Diagnostic performance of attenuation coefficient measurement was evaluated using receiver operating characteristic (ROC) curve analysis with calculation of the area under the curve (AUC), sensitivity, specificity, and optimal cut-off values. Comparative analyses were performed to assess differences in diagnostic accuracy between attenuation coefficient measurement and the hepatorenal index. Economic evaluation was conducted from the healthcare provider perspective and included estimation of the cost per correct diagnosis, the cost-to-accuracy ratio (cost/AUC), and the incremental cost-effectiveness ratio (ICER), based on representative market prices of diagnostic procedures in Ukraine. Results. Attenuation coefficient measurement demonstrated high diagnostic accuracy for the detection of hepatic steatosis, with an AUC of 0.94 (95% confidence interval 0.88–0.96), significantly exceeding the diagnostic performance of the hepatorenal index. The method enabled reliable discrimination between different grades of steatosis using predefined cut-off values, with sensitivity and specificity exceeding 80% for clinically relevant steatosis. Attenuation coefficient values showed a strong and statistically significant association with MRI-PDFF, confirming the ability of this ultrasound-based method to quantitatively reflect hepatic fat content. Diagnostic performance of attenuation coefficient measurement remained stable across patient subgroups, including individuals with elevated body mass index, indicating reduced dependence on anthropometric factors compared with other ultrasound-based approaches. Decision curve analysis demonstrated that attenuation coefficient measurement provided the highest net clinical benefit across clinically relevant threshold probabilities for referral, outperforming controlled attenuation parameter–based elastography and MRIPDFF in primary screening scenarios. From an economic perspective, attenuation coefficient measurement showed the most favourable efficiency profile among the evaluated non-invasive diagnostic modalities. The cost per unit of diagnostic accuracy (cost/AUC) was substantially lower for attenuation coefficient measurement than for controlled attenuation parameter–based elastography and magnetic resonance imaging with proton density fat fraction (MRI-PDFF). Modelling of population-level screening scenarios indicated that the use of attenuation coefficient measurement as a first-line screening tool could reduce overall diagnostic expenditures by approximately 70–85% while maintaining high sensitivity for clinically significant hepatic steatosis. Conclusions. Ultrasound attenuation coefficient measurement is a diagnostically accurate, accessible, and economically feasible method for the primary screening of metabolically associated steatotic liver disease. Integration of this method into routine liver ultrasound examinations may improve early identification of hepatic steatosis, support appropriate patient stratification, and optimize the use of healthcare resources, particularly at the level of primary healthcare and in health systems with limited budgets.