首页|临床及MRI列线图模型预测直肠癌同时性肝转移

临床及MRI列线图模型预测直肠癌同时性肝转移

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目的 观察基于临床及MRI表现建立的列线图模型预测直肠癌同时性肝转移(SLM)的价值.方法 按7∶3随机将356例直肠癌临床及MRI资料分为训练集(n=249,45例SLM)与验证集(n=107,27例SLM),以logistic回归分析筛选预测直肠癌SLM的独立因素,构建列线图模型并评价其效能.结果 肿瘤N分期、血清癌胚抗原、糖类抗原19-9及直肠系膜筋膜(MRF)受累与否均为预测直肠癌SLM的独立因素.以此构建的列线图模型预测训练集与验证集直肠癌SLM的曲线下面积分别为0.834[95%CI(0.776,0.893)]及0.769[95%CI(0.662,0.877)];且校准曲线显示预测值与实测值的一致性良好,决策曲线分析显示列线图模型具有较好临床实用性.结论 基于临床及MRI特征建立的列线图模型可用于预测直肠癌SLM.
Clinical and MRI nomogram model for predicting simultaneous liver metastasis of rectal cancer
Objective To explore the value of nomogram model based on clinical data and MRI findings for predicting simultaneous liver metastasis(SLM)of rectal cancer.Methods Clinical and MRI data of 356 patients with rectal cancer were randomly divided into training set(n=249,45 cases of SLM)and validation set(n=107,27 cases of SLM)at a ratio of 7∶3.Logistic regression analysis were used to screen the independent factors for predicting SLM of rectal cancer.The nomogram model was then constructed,and the efficacy of this model was evaluated.Results Tumor N-stage,serum carcinoembryonic antigen,carbohydrate antigen 19-9 and involvement of mesorectal fascia(MRF)or not were all independent factors for predicting SLM of rectal cancer.The area under the curve(AUC)of this nomogram model for predicting rectal cancer SLM in training set and validation set was 0.834(95%CI[0.776,0.893])and 0.769(95%CI[0.662,0.877]),respectively.The calibration curve showed good consistency between the predicted values and the measured values,and the decision curve analysis showed that the nomogram model had good clinical practicality.Conclusion The nomogram model based on clinical data and MRI findings could be used to predict SLM of rectal cancer.

rectal neoplasmsneoplasm metastasismagnetic resonance imaging

潘玉蝶、王书兴、刘晓雯、徐婷、江长思、唐雪、罗燕、龚静山

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暨南大学第二临床医学院,广东 深圳 518020

深圳市人民医院(暨南大学第二临床医学院,南方科技大学第一附属医院)放射科,广东 深圳 518020

直肠肿瘤 肿瘤转移 磁共振成像

2024

中国医学影像技术
中国科学院声学研究所

中国医学影像技术

CSTPCD北大核心
影响因子:0.763
ISSN:1003-3289
年,卷(期):2024.40(9)