Multimodal models established combined 18F-FDG PET/CT radiomics with clinical data for evaluating response of locally advanced head and neck squamous cell carcinoma to neoadjuvant immuno-chemotherapy
10.13929/j.issn.1003-3289.2024.10.008
- VernacularTitle:18F-FDG PET/CT联合临床建立多模态影像组学模型预测局部晚期头颈部鳞癌对于新辅助免疫联合化学治疗的反应
- Author:
Rong HUANG
1
;
Xiaoxu LU
;
Xueming SUN
;
Hui WU
Author Information
1. 郑州大学附属肿瘤医院(河南省肿瘤医院)放疗科,河南郑州 450008
- Keywords:
carcinoma,squamous cell;
head;
neck;
neoadjuvant therapy;
positron-emission tomography;
tomography,X-ray computed;
fluorodeoxyglucose F18;
radiomics
- From:
Chinese Journal of Medical Imaging Technology
2024;40(10):1493-1498
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of multimodal models established combined 18F-FDG PET/CT radiomics with clinical data for evaluating response of locally advanced head and neck squamous cell carcinoma(LA-HNSCC)to neoadjuvant immuno-chemotherapy.Methods Totally 213 LA-HNSCC patients were retrospectively enrolled and randomized into training set(n=170)and test set(n=43)at the ratio of 8∶2.Radiomics features of tumors on 18F-FDG PET/CT were extracted and selected from training set,and the independent clinical predictors were screened with sequential univariate and multivariate logistic regressions.Radiomics models,clinical models and combined multimodal models were constructed using different algorithms,including adaptive boosting(AdaBoost),decision tree,naive Bayes,random forest(RF),support vector machine(SVM)and extreme gradient boosting(XGBoost),respectively.The receiver operating characteristic(ROC)curves were drawn,and the area under the curves(AUC)were calculated to assess the efficacy of each model for predicting the response of LA-HNSCC to neoadjuvant immuno-chemotherapy,and the decision curve analysis(DCA)was performed to explore the net benefit of each model.Results Totally 110 radiomics features were selected,and CD4/CD8 ratio was the independent clinical predictor of the response of LA-HNSCC to neoadjuvant immuno-chemotherapy.Models based on AdaBoost and XGBoost algorithms had high and stable efficacy for predicting tumor response to neoadjuvant immuno-chemotherapy,among which the multimodal models had better performance(AUC=0.943,0.930)than radiomics models(AUC=0.939,0.925)and clinical models(AUC=0.903,0.910)in test set(all P＜0.05).Conclusion Multimodal models established combined 18F-FDG PET/CT radiomics with CD4/CD8 ratio were more effective for predicting response of LA-HNSCC to neoadjuvant immuno-chemotherapy than any single model.
