A Model Based on Computed Tomography Imaging Parameters to Predict Poor Survival in Patients With Liver Cirrhosis

Cirrosis, which is always manifesting as ascites, hepatic encephalopathy, upper gastrointestinal bleeding, severe jaundice and coagulopathy, deteriorates rapidly with a high mortality. Early identification and accurate predicted model may be the key to make duly clinical decision and improve prognosis. When hepatic disorders accur, cirrhosis is often accompanied by varying degrees of malnutrition, which is accurately reflexed by the cross-sectioned areas of the muscles at the third lumbar vertebra level normalized by the square of the height （L3-SMI）. In addition, previous studies have shown that lower density of adiposity and altered liver volume were often associated with adverse clinical events. These changes in body composition can be accurately assessed and measured by using CT scans. However, there is no ideas whether these imaging patameters are reliable indicators to predict the mortality of cirrhosis. In this study, we aimed to evaluate the difference of serial changes of L3-SMI, the density of adiposity and liver volume between 5-year survival and non-survival group and develop a new prognostic model based on these CT imaging data. This study highlighted the clinical significance of serial changes of CT imaging data in predicting the long-term outcome of patients with cirrhosis for the first time.