国际医学放射学杂志2024，Vol.47Issue(3)：280-287,8.DOI:10.19300/j.2024.L21231
基于临床及CT影像组学模型早期预测结直肠癌肝转移的化疗反应
Early prediction of chemotherapy response in colorectal cancer liver metastasis based on clinical and CT radiomics models
摘要
Abstract
Objective To investigate the value of a combined model based on clinical,pathological,and CT radiomics features in early predicting chemotherapy response in colorectal cancer liver metastasis(CRLM).Methods Clinical,pathological,and contrast-enhanced CT imaging data of 169 patients with CRLM were retrospectively collected.One liver metastatic lesion was randomly selected from each patient,totaling 169 lesions.Lesions were divided into two groups according to Response Evaluation Criteria in Solid Tumors(RECIST):chemotherapy responsive group(75 lesions)and chemotherapy non-responsive group(94 lesions).Lesions were randomly divided into training set(118 lesions)and validation set(51 lesions)in a 7∶3 ratio.Radiomics features of lesions in baseline portal venous phase CT images were extracted.Optimal radiomics features were selected using Pearson correlation coefficient,Select Percentile univariate analysis,and Least Absolute Shrinkage and Selection Operator(LASSO).A radiomics model was constructed using logistic regression classifier,and radiomics score(Radscore)was calculated.Clinical and pathological features with statistically significant differences between the two groups were selected using t-tests,Mann-Whitney U tests,and Chi-square tests.Clinical-pathological model and combined model were constructed by integrating selected features with Radscore.The predictive performance,calibration,and goodness-of-fit of the models were evaluated using receiver operating characteristic(ROC)curve,calibration curve,and Hosmer-Lemeshow test.Nomogram were constructed based on the predictive indicators of the combined model.Results Nine optimal radiomics features,three clinical and pathological features(type of liver metastasis,carcinoembryonic antigen,and RAS gene)were selected.In the training and validation sets,the predictive efficacy of the combined model for chemotherapy response in liver metastatic lesions(AUC=0.896,0.798)was similar to the radiomics model(AUC=0.895,0.786),with no statistically significant difference(all P＞0.05).In the training set,the predictive efficacy of the combined model for chemotherapy response in liver metastatic lesions was higher than the clinical-pathological model(P＜0.05),while in the validation set,there was no statistically significant difference compared to the clinical-pathological model(P＞0.05).Calibration curve and Hosmer-Lemeshow test showed good calibration and fit of the Nomogram of the combined model.Conclusion The radiomics model based on CT imaging features before chemotherapy can early predict chemotherapy response in CRLM.Integration of clinical and pathological features can slightly improve the predictive performance of the model.关键词
结直肠癌/肝转移瘤/影像组学/疗效评估/体层摄影术,X线计算机Key words
Colorectal cancer/Liver metastases/Radiomics/Efficacy assessment/Tomography,X-ray computed分类
医药卫生引用本文复制引用
袁隆,李昇霖,卢婷,徐敏,杨晶晶,席华泽,周俊林..基于临床及CT影像组学模型早期预测结直肠癌肝转移的化疗反应[J].国际医学放射学杂志,2024,47(3):280-287,8.基金项目
国家自然科学基金项目(82071872,82371914) （82071872,82371914）
