Construction and validation of a prediction model for Ki-67 expression in hepatocellular carcinoma patients using MRI features combined with clinical indicators
HE Yuqing
YANG Yi
YAO Dinghua
YANG Chun
WENG Jingfei
Abstract：Objective To develop a preoperative model combining MRI features and clinical variables for predicting high Ki-67 expression in hepatocellular carcinoma(HCC)and to assess its prognostic value.Methods A total of 344 patients with solitary HCC who underwent hepatectomy at Zhongshan Hospital,Fudan University from January to December 2020 were retrospectively enrolled.Among them,191 patients showed high Ki-67 expression(>25%)and 153 patients had low Ki-67 expression(≤25%)based on postoperative pathological findings.Preoperative MRI features,clinical variables,and pathological data were collected,and each HCC lesion was assigned a LI-RADS.The relationship between MRI,clinical,and pathological features and high Ki-67 expression was compared.The model's performance was evaluated using ROC curves,and the recurrence-free survival(RFS)was compared using the Kaplan-Meier method.Results Multivariable logistic regression identified age and lower alpha-fetoprotein(AFP)as protective factors,whereas high Edmondson-Steiner grade,corona enhancement and LI-RADS were independent risk factors for high Ki-67(P<0.05).A composite score incorporating these five variables yielded an AUC of 0.747(sensitivity 68.1%,specificity 71.9%),outperforming any single predictor(P<0.05).Overall RFS did not differ between high and low Ki-67 groups(P>0.05).Among patients with high Ki-67,those with microvascular invasion had significantly shorter RFS than those without microvascular invasion(P<0.05);no such difference was observed in the low Ki-67 subgroup(P>0.05).Conclusion Preoperative MRI features(corona enhancement,LI-RADS)combined with clinical variables(age,AFP,Edmondson-Steiner grade)reliably predict high Ki-67 expression in HCC and provide imaging evidence for prognostic stratification.
Keywords：hepatocellular carcinomamagnetic resonance imagingKi-67
Publication Date：2025-10-20
Online Publishing Date：2025-11-24(First online date of this platform, not the publication date of the document)
Pages：8( 1205-1212 )