From 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.).
Radiology. 2015 Aug;276(2):433-43. doi: 10.1148/radiol.15142394. Epub 2015 Mar 4.
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.
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).
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).
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.
确定磁共振成像(MR)特征,以便预测肝癌(HCC)根治性切除术后早期复发(<2 年),并建立术前预测模型。
本回顾性研究经机构审查委员会批准,豁免了书面知情同意书的要求。纳入 2008 年 1 月至 2011 年 8 月期间因单个 HCC 行肝切除术的 268 例患者,分为训练队列(n=187)和验证队列(n=81)。训练队列的所有 MR 图像均由 2 位放射科医生进行回顾。采用多元逻辑回归分析,筛选与早期复发独立相关的 MR 成像特征,建立预测模型。采用验证队列评估预测模型的鉴别能力(即个体预测的后续早期复发的相对排序是否正确)。
在训练队列中,有 4 项 MR 成像特征与早期复发独立相关:边缘强化(比值比[OR] =3.83;95%置信区间[CI]:1.3910.52)、动脉期肿瘤周围实质强化(OR=2.64;95%CI:1.275.46)、卫星结节(OR=4.07;95%CI:1.0915.21)和肿瘤大小(OR=1.66;95%CI:1.312.09)。基于这些变量建立的预测模型,在训练队列中预测早期复发风险的受试者工作特征曲线下面积(AUC)为 0.788。将该模型应用于验证队列时,具有良好的鉴别能力(AUC=0.783)。
基于边缘强化、肿瘤周围实质强化、卫星结节和肿瘤大小建立的预测模型,可用于术前评估单个 HCC 切除术后早期复发的风险。