Objective To study the risk factors of microvascular invasion(MVI)in patients with early liver cancer by computed tomography(CT)imaging and magnetic resonance imaging(MRI).Methods A retrospective study was con-ducted on 96 patients with early liver cancer admitted to our hospital from January 2022 to December 2023.The patients with early liver cancer were divided into the occurrence group and the non-occurrence group according to the medical record system,and the clinical and imaging data of the two groups were collected and compared.Logistic regression model was a-dopted to analyze the factors affecting the occurrence of MVI in patients with early liver cancer.The risk prediction nomo-gram model was constructed,and the value of the prediction model was evaluated by receiver operating characteristic curve(ROC curve).Calibration curve and decision curve were constructed to verify the value of the prediction model.Results According to the records of the medical records system,20 of the 96 patients with early liver cancer developed MVI,ac-counting for 20.83％(20/96),and they were divided into the occurrence group;76 patients did not develop MVI,account-ing for 79.17％(76/96),and they were divided into the non-occurrence group.There were significant differences in tumor diameter,abnormal peritumoral enhancement,tumor morphology,incomplete pseudoenvelope,and peritumoral low signal in hepatobiliary stage between the two groups(P＜0.05),and the above parameters were all associated risk factors for MVI in patients with early liver cancer(OR value＞1).According to the Logistic regression model to build a nomogram risk prediction model,it can be seen that all factors have a certain degree of prediction value.The ROC curve was constructed to verify the accuracy of the nomogram prediction effect,and it was found that the AUC was 922,95％CI was(0.857-0.987),indicating that the risk prediction model was of high value.The calibration curve and reference curve of the risk prediction model were similar,which proved that there was a high consistency between the predicted risk and the actual risk of MVI occurrence in early liver cancer patients.At the same time,the net benefit rate of the prediction model in the thresh-old range is higher,which proves that the applicability of the prediction model is better.Conclusion Tumor diameter,ab-normal peritumoral enhancement,tumor morphology,incomplete pseudoenvelope and low peritumoral signal in hepatobiliary stage are all independent factors influencing the occurrence of MVI in patients with early liver cancer,which can be used as important indicators to predict the occurrence of MVI.Imaging findings can effectively screen high-risk groups and provide theoretical guidance for clinical practice.
Early liver cancerComputed tomography imagingMagnetic resonance imagingMicrovascular invasionRisk factor
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