2092110 Correlation Between Controlled Attenuation Parameter(CAP) and Liver Steatosis Quantification

The CAP based on Fibroscan® has been recently developed for liver steatosis assessment. This study was designed to evaluate the utility of CAP using the diagnostic cut-offs proposed by the Shi meta-analysis (1). Steatosis was evaluated using CAP and ultrasound in 570 subjects. CAP was calculated if valid liver stiffness measurements were obtained by M probe, expressed in decibel per meter (dB/m). CAP failure was defined as zero valid shots. For quantification between different stages of steatosis we used the following cut-off values: S1=232.5 db/m, S2=255 db/m, S3=290 db/m(1). The severity of liver steatosis was evaluated by ultrasound as according to the subjective assessment of the “brightness” of the liver and the intensity of “posterior attenuation”. A semi-quantitative scale was used, ranging from 0 to 3 (0, no steatosis; 1, mild steatosis; 2, moderate steatosis; 3, severe steatosis). The US examination was performed by expert ultrasonographists (level III according to the EFSUMB classification), blinded to CAP quantification. 38,9% (222 subjects), were excluded due to failure/unrealiable liver stiffness measurements with M probe. In ultrasound, liver steatosis was graded as follows: S0- 144 cases (41.4%), S1 - 94 cases (27%), moderate – 85 cases (24.5%) and severe - 27 cases (7.2%). By using the proposed cut-off values, there were no significant differences in percentages between CAP values and quantification of steatosis by means of US in patients without steatosis (36.8% vs 41.4% p=0.4), in patients with mild ( 11.5% vs 24.4 % p=0.08) or with moderate steatosis (18.7% vs 24,5% p=0.2). Only severe steatosis was observed in a significantly higher percentage by means of CAP than by ultrasound (33% vs 7.2 % p<0.001). CAP showed good correlation with steatosis estimated by ultrasound (r=0.6072, p<0.0001). CAP seems to be a promising tool for screening and quantification of steatosis in the general population. Larger studies are needed for validation.