New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma

The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images.

This retrospective study included 86 consecutive patients with HCC who underwent surgical resection between January 2000 and September 2008. The arterial- and portal-phase dynamic CT images obtained preoperatively were classified into four enhancement patterns: Type-1 and Type-2 are homogeneous enhancement patterns without or with increased arterial blood flow, respectively; Type-3, heterogeneous enhancement pattern with septum-like structure; and Type-4, heterogeneous enhancement pattern with irregular ring-like structures. We also evaluated the predictive factors for poorly-differentiated HCC, specific macroscopic type of HCC (simple nodular type with extranodular growth [SNEG] and confluent multinodular [CMN]) by univariate and multivariate analyses.

The percentages of poorly-differentiated HCC according to the enhancement pattern were three of 51 nodules (6%) of Type-1 and -2, three of 24 (13%) of Type-3, and eight of 11 (73%) of Type-4. The percentages of SNEG/CMN according to the enhancement pattern were 12 of 51 nodules (24%) of Type-1 and -2, 13 of 24 (54%) of Type-3, and five of 11 (45%) of Type-4. Multivariate analysis identified Type-4 pattern as a significant and independent predictor of poorly-differentiated HCC (P < 0.001) while Type-3 pattern was a significant predictor of SNEG/CMN (P = 0.017).

Heterogeneity of dynamic CT images correlates with malignant characteristics of HCC and can be potentially used to predict the malignant potential of HCC before treatment.