基于磁共振成像机器学习算法和影像组学构建预测模型预测无淋巴结转移直肠癌淋巴血管侵犯状态的应用价值  

Application value of prediction model based on magnetic resonance imaging machine learning algorithm and radiomics in predicting lymphovascular invasion status of rectal cancer without lymph node metastasis

作　　者：彭乐平 张秀玲 朱袁慧 王玲[3] 马文婷 马娅琼[2] 黄刚[2] 王莉莉[2] Peng Leping;Zhang Xiuling;Zhu Yuanhui;Wang Ling;Ma Wenting;Ma Yaqiong;Huang Gang;WangLili(The First School of Clinical Medical,Gansu University of Chinese Medicine,Lanzhou 730099,China;Department of Radiology,Gansu Provincial Hospital,Lanzhou 730099,China;Department of Pathology,Gansu Provincial Hospital,Lanzhou 730099,China)

机构地区：[1]甘肃中医药大学第一临床医学院,兰州730099 [2]甘肃省人民医院放射科,兰州730099 [3]甘肃省人民医院病理科,兰州730099

出　　处：《中华消化外科杂志》2024年第8期1099-1111,共13页Chinese Journal of Digestive Surgery

基　　金：甘肃省青年科技基金计划项目(20JR5RA143);甘肃省人民医院院内科研基金项目(23GSSYF-4、23GSSYA-2)。

摘　　要：目的基于磁共振成像(MRI)机器学习算法和影像组学构建预测模型,探讨模型预测无淋巴结转移直肠癌患者淋巴血管侵犯(LVI)状态的应用价值.方法采用回顾性队列研究方法.收集2016年2月至2024年1月甘肃省人民医院收治204例无淋巴结转移直肠癌患者的临床病理资料;男123例,女81例;年龄为(61±7)岁.204例患者采用电子计算器随机法按8∶2随机分为训练集163例和测试集41例.训练集用于构建预测模型,测试集用于验证预测模型效能.根据筛选的临床和(或)影像学特征分别构建临床预测模型、影像组学模型、联合预测模型.正态分布的计量资料以(x)±s表示.计数资料以绝对数表示,组间比较采用χ^(2)检验或Fisher确切概率法.等级资料比较采用非参数秩和检验.采用组间相关系数评估2位医师影像组学特征的一致性,相关系数>0.80认为一致性较好.单因素分析采用相应的统计学方法.多因素分析采用Logistic逐步回归模型.绘制受试者工作特征(ROC)曲线,以曲线下面积(AUC)及Delong检验、决策曲线和临床影响曲线评估模型的诊断效能及临床效用.结果(1)影响患者LVI状态的因素分析.204例无淋巴结转移直肠癌患者中,LVI阳性71例,LVI阴性133例.多因素分析结果显示:性别、血小板(PLT)计数和癌胚抗原(CEA)是影响训练集无淋巴结转移直肠癌患者LVI状态的独立因素[优势比=2.405,25.062,2.528,95%可信区间(CI)为1.093~5.291,2.748~228.604,1.181~5.410,P<0.05].(2)临床预测模型建立.纳入多因素分析结果性别、PLT计数和CEA构建临床预测模型.ROC曲线显示:临床预测模型训练集的AUC、准确度、灵敏度、特异度分别为0.721(95%CI为0.637~0.805)、0.675、0.632、0.698;测试集上述指标分别为0.795(95%CI为0.644~0.946)、0.805、1.000、0.429.Delong检验结果显示:训练集和测试集AUC比较,差异无统计学意义(Z=-0.836,P>0.05).(3)影像组学模型建立.提取204例患者851�Objective To construct an prediction model based on magnetic resonance imaging(MRI)machine learning algorithm and radiomics and investigate its application value in predicting lymphovascular invasion(LVI)status of rectal cancer without lymph node metastasis.Methods The retrospective cohort study was conducted.The clinicopathological data of 204 rectal cancer patients without lymph node metastasis who were admitted to Gansu Provincial Hospital from February 2016 to January 2024 were collected.There were 123 males and 81 females,aged(61±7)years.All 204 patients were randomly divided into the training dataset of 163 cases and the testing dataset of 41 cases by a ratio of 8:2 using the electronic computer randomization method.The training dataset was used to construct the prediction model,and the testing dataset was used to validate the prediction model.The clinical prediction model,radiomics model and joint prediction model were constructed based on the selected clinical and/or imaging features.Measurement data with normal distribution were represented as Mean+SD.Count data were described as absolute numbers,and the chi-square test or Fisher exact probability were used for comparison between the groups.Comparison of ordinal data was conducted using the nonparameter rank sum test.The inter-class correlation coefficient(ICC)was used to evaluate the consistency of the radiomics features of the two doctors,and ICC>0.80 was good consistency.Univariate analysis was conducted by corres-ponding statistic methods.Multivariate analysis was conducted by Logistic stepwise regression model.The receiver operating characteristic(RoC)curve was drawn,and the area under the curve(AUC),Delong test,decision curve and clinical impact curve were used to evaluate the diagnostic efficiency and clinical utility of the model.Result(1)Analysis of factors affecting LVI status of patients.Of the 204 rectal cancer patients without lymph node metastasis,there were 71 cases with positive of LVI and 133 cases with negative of LVI.Results of multiv

关 键 词：直肠肿瘤 磁共振成像 影像组学 机器学习 淋巴血管侵犯 

分 类 号：R445.2[医药卫生—影像医学与核医学] R735.37[医药卫生—诊断学]