摘要
目的研究CT影像与MRI表现在早期肝癌患者微血管侵犯(MVI)发生的危险因素分析。方法选取2022年1月至2023年12月本院接收的早期肝癌患者96例进行回顾性研究,依据病历系统记录早期肝癌患者是否发生MVI分为发生组、未发生组,搜集对比两组患者临床相关资料及影像学信息。针对差异指标采取Logistic回归模型分析早期肝癌患者MVI发生的影响因素,构建风险预测列线图模型,利用受试者工作特征曲线(ROC曲线)评价预测模型的价值,构建校准曲线与决策曲线,验证预测模型的价值。结果96例早期肝癌患者中20例发生MVI,占比20.83%(20/96)。76例患者未发生MVI,占比79.17%(76/96)。两组患者肿瘤直径、瘤周异常强化、肿瘤形态、假包膜不完整、肝胆期瘤周低信号对比存在显著差异(P<0.05),且上述参数均为早期肝癌患者发生MVI的相关危险因素(OR值>1)。依据采取Logistic回归模型构建列线图风险预测模型可知,各因素均具有一定程度的预测价值,通过构建ROC曲线,验证列线图预测效果的准确性,发现其曲线下面积(AUC)是0.922,95%CI为(0.857~0.987),由此表明该风险预测模型价值较高。风险预测模型的校准曲线和参考曲线相近,表明早期肝癌患者MVI发生的预测风险和实际风险存在较高的一致性;同时阈值范围中预测模型的净获益率较高,证明该预测模型的适用性较好。结论肿瘤直径、瘤周异常强化、肿瘤形态、假包膜不完整、肝胆期瘤周低信号均为早期肝癌患者MVI发生的独立影响因素,能够作为预测MVI发生的重要指标。通过影像学表现有效筛查高危群体,为临床实践提供理论指导。
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 conducted 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 adopted to analyze the factors affecting the occurrence of MVI in patients with early liver cancer.The risk prediction nomogram 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,accounting for 20.83%(20/96),and they were divided into the occurrence group;76 patients did not develop MVI,accounting 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 threshold range is higher,which proves that the applicability of the prediction model is better.Conclusion Tumor diameter,abnormal 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.
作者
徐天才
XU Tiancai(Radiology Department of Jianli People’s Hospital,Jianli,Hubei Province 433332,P.R.China)
出处
《临床放射学杂志》
北大核心
2024年第9期1523-1528,共6页
Journal of Clinical Radiology
关键词
早期肝癌
计算机断层扫描成像
磁共振成像
微血管侵犯
危险因素
Early liver cancer
Computed tomography imaging
Magnetic resonance imaging
Microvascular invasion
Risk factor
