Differentiation of regenerative nodule, dysplastic nodule, and small hepatocellular carcinoma in cirrhotic patients: a contrast-enhanced ultrasound-based multivariable model analysis.

Abstract

To develop a contrast-enhanced ultrasound (CEUS)-based model for differentiating cirrhotic liver lesions and for active surveillance of hepatocellular carcinoma (HCC). Patients with focal liver lesions (FLLs) with biopsy/resection-proven pathology and pre-procedure CEUS were enrolled from our institution between January 2011 and November 2014. Univariable and multivariable regression models were constructed using qualitative CEUS features and/or contrast arrival time ratio (CAT_R). The optimism-adjusted Harrell's generalized concordance index (C_H) was used to quantify the discriminatory ability of each CEUS feature and model. A total of 149 patients (113 men and 36 women) with 162 FLLs were enrolled with mean age 53.4 ± 12.7 years. A 0.1-unit reduction in CAT_R was associated with a 68% increase in the odds of having a higher nodule ranking (RN < DN < small HCC) (OR, 0.32; 95% CI, 0.20-0.50, p < .001). Arterial phase hypoenhancement and isoenhancement were inversely associated with a higher nodule ranking compared to hyperenhancement. Late-phase isoenhancement was associated with lower odds of a higher nodule ranking. The CEUS + CAT_R model (C_H 0.92, 0.89-0.95) provided greater discriminatory ability when compared to the CAT_R model (ΔC_H 0.09, 0.04-0.13, p < .001) and the CEUS model (ΔC_H 0.03, 0.01-0.05, p = .02). Our results provide preliminary evidence that multivariable regression model constructed using both qualitative CEUS features and CAT_R provides the greatest discriminatory ability to differentiate RN, DN, and small HCC in patients with cirrhosis, and might allow for active surveillance of the progression of cirrhotic liver lesions. • Proportional odds logistic regression models based on qualitative CEUS features and/or CAT_R can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC. • The reduction of CAT_R (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules. • Inclusion of CAT_R in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.