Preoperative prediction of hepatocellular carcinoma with highly aggressive characteristics using quantitative parameters derived from hepatobiliary phase MR images.

Abstract

To prospectively determine whether the quantitative imaging parameters derived from the hepatobiliary phase (HBP) can be used for the preoperative prediction of hepatocellular carcinoma (HCC) with highly aggressive characteristics. One hundred and three patients with surgical-proven HCC were included from July 2015 to June 2018. Two independent reviewers measured signal intensity (SI) of liver and tumor, and quantitative parameters, including relative tumor enhancement (RTE), tumor to liver contrast ratio (TLR), tumor enhancement index (TEI), and relative enhancement ratio (RER) were calculated. The aggressive characteristics of HCC were identified by using the Ki-67 labeling index (LI), and patients were classified into low aggressive (Ki-67 LI ≤10%) and high aggressive (Ki-67 LI >10%) groups. The difference of quantitative parameters between two groups was assessed, and the correlation between quantitative parameters and Ki-67 LI was explored. Receiver operating characteristic analyses was used to evaluate the predictive performance of quantitative parameters. The values of RTE, TLR, TEI, and RER, were significantly lower in the highly aggressive group than low aggressive group (P<0.05), and negative correlations were obtained between these quantitative parameters and Ki-67 LI (r ranges from -0.41 to -0.22, P<0.05). TLR demonstrated the highest predictive performance with the area under curve (AUC) of 0.83 [95% confidence interval (CI): 0.75-0.90], sensitivity of 89.0% and specificity of 63.3%, and subsequent with RER, TEI, and RTE with AUC of 0.78 (95% CI: 0.68-0.85), 0.74 (95% CI: 0.64-0.82) and 0.68 (95% CI: 0.58-0.77), respectively. Good inter-observer and intra-observer agreement were found in all parameters. TLR showed the highest predictive performance in highly aggressive HCC. Quantitative parameters based on HBP could preoperatively predict the aggressiveness of HCC.