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Single Hepatocellular Carcinoma: Preoperative MR Imaging to Predict Early Recurrence after Curative Resection
Chansik An1, Dong Wook Kim1, Young-Nyun Park1
1From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.).
Purpose:
To identify magnetic resonance (MR) imaging features that enable prediction of early recurrence (<2 years) after curative resection of hepatocellular carcinoma (HCC) and to derive a preoperative prediction model.
Materials And Methods:
This retrospective study was approved by the institutional review board. The requirement to obtain written informed consent was waived. A total of 268 patients who underwent hepatic resection for a single HCC from January 2008 to August 2011 were divided into two cohorts: a training cohort, which was used to derive a prediction model (n = 187), and a validation cohort (n = 81). All MR images from the training cohort were reviewed by two radiologists. A prediction model was constructed by using MR imaging features that were independently associated with early recurrence with use of multiple logistic regression analysis. The performance of the prediction model in the validation cohort was evaluated with respect to discrimination (ie, whether the relative ranking of individual predictions of subsequent early recurrence is in the correct order).
Results:
In the training cohort, four MR imaging features were independently associated with early recurrence: rim enhancement (odds ratio [OR] = 3.83; 95% confidence interval [CI]: 1.39, 10.52), peritumoral parenchymal enhancement in the arterial phase (OR = 2.64; 95% CI: 1.27, 5.46), satellite nodule (OR = 4.07; 95% CI: 1.09, 15.21), and tumor size (OR = 1.66; 95% CI: 1.31, 2.09). A prediction model derived from these variables showed an area under the receiver operating characteristic curve (AUC) of 0.788 in the prediction of the risk of early recurrence in the training cohort. When applied to the validation cohort, this model showed good discrimination (AUC, 0.783).
Conclusion:
The prediction model derived from rim enhancement, peritumoral parenchymal enhancement, satellite nodule, and tumor size can be used preoperatively to estimate the risk of early recurrence after resection of a single HCC.
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