分子影像学杂志2025，Vol.48Issue(3)：315-322,8.DOI:10.12122/j.issn.1674-4500.2025.03.10
深度学习模型与机器学习模型在术前预测结直肠癌错配修复系统分型表现的对比:基于CT影像组学
Comparison of deep learning models and machine learning models in pre-operative prediction of mismatch repair system classification for colorectal cancer:based on CT radiomics
摘要
Abstract
Objective To establish a variety of machine learning models based on CT radiomics features and deep learning models based on convolutional neural networks,to compare the performance of the two methods in predicting the preoperative mismatch repair(MMR)typing model in colorectal cancer(CRC)patients.Methods A retrospective study was conducted on 120 colorectal cancer patients who were randomly divided into 7:3 into the training group and the test group,and all of these cases were from the First Affiliated Hospital of Hebei North University.The region of interest(ROI)was plotted and the radiomics features were extracted to select the optimal set.The machine learning models were builded including random forests,support vector machines and logistic regression algorithms,as well as deep learning convolutional neural network(CNN)structures Vgg16 models.The diagnostic performance of the model was evaluated by the area under the ROC curve(AUC),sensitivity,accuracy,specificity and F1 score.Results The AUC values of the test group of the three machine learning models were 0.82(95%CI:0.75-0.84),0.75(95%CI:0.73-0.81),and 0.71(95%CI:0.59-0.74),and the F1 scores were 0.60,0.82,and 0.57.The test group AUC of the deep learning model was 0.87(95%CI:0.76-0.91)and the F1 score was 0.82.Conclusion The radiomics machine learning and deep learning models based on CT images can effectively identify the MMR typing of colorectal cancer.According to the AUC values obtained by different models,it is found that the deep learning model is more efficient than the machine learning model in identifying the two types of MMR.关键词
结直肠癌/错配修复系统/影像组学/深度学习/随机森林Key words
colorectal cancer/mismatch repair system/radiomics/deep learning/random forest引用本文复制引用
王梓萌,王文江,王大伟,崔书君..深度学习模型与机器学习模型在术前预测结直肠癌错配修复系统分型表现的对比:基于CT影像组学[J].分子影像学杂志,2025,48(3):315-322,8.基金项目
河北省医学科学研究课题计划(20220585) （20220585）
