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Updated: Sep 2, 2025

Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH
Published on: April 20, 2021
Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver
Hanying Liu1, Xiao Li2, Xiaodong Han3
1Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
Objective:
Non-alcoholic fatty liver disease (NAFLD) is one of the leading causes of chronic liver disease. The controlled attenuation parameter (CAP) obtained by FibroScan reflects the level of liver steatosis in patients with obesity. Our study aimed to construct a simple equation to predict the CAP, to facilitate the screening and monitoring of patients at high risk for NAFLD.
Methods:
A total of 272 subjects were randomly divided into derivation and validation cohorts at a ratio of 1:2. The derivation set was used for constructing a multiple linear regression model; the validation set was used to verify the validity of the model.
Results:
Several variables strongly correlated with the CAP were used to construct the following equation for predicting CAP values:CAP1 = 2.4 × BMI + 10.5 × TG+ 3.6 × NC + 10.3 × CP +31.0, where BMI is body mass index, TG is triglyceride, NC is neck circumference and CP is C-peptide. The CAP1 model had an R 2 of 0.764 and adjusted R 2 of 0.753. It was then simplified to derive CAP2 included only simple anthropometric parameters: CAP2 = 3.5 × BMI + 4.2 × NC + 20.3 (R 2 = 0.696, adjusted R 2 = 0.689). The data were well fitted by both models. In the verification group, the predicted (CAP1 and CAP2) values were compared to the actual CAP values. For the CAP1 equation, R 2 = 0.653, adjusted R 2 = 0.651. For the CAP2 equation, R 2 = 0.625, adjusted R 2 = 0.623. The intra-class correlation coefficient (ICC) values were 0.781 for CAP1 and 0.716 for CAP2 (p < 0.001). The actual CAP and the predicted CAP also showed good agreement in Bland-Altman plot.
Conclusion:
The equations for predicting the CAP value comprise easily accessible variables, and showed good stability and predictive power. Thus, they can be used as simple surrogate tools for early screening and follow-up of NAFLD in the Chinese population.

