扩散加权成像模型影像组学特征预测食管鳞癌病人总生存期的价值OA

Objective To compare the value of radiomic features derived from three diffusion-weighted imaging(DWI)models in predicting overall survival(OS)in patients with esophageal squamous cell carcinoma(ESCC).Methods Ninety patients with pathologically confirmed ESCC were retrospectively included(mean age,64.9±7.2 years;median follow-up,42 months).DWI was acquired at 3.0 T using 12 b values(0-2 000 s/mm²).Tumor regions of interest(ROIs)were delineated on T2-weighted images(T2WI),registered to DWI-derived parametric maps from the monoexponential apparent diffusion coefficient(Mono-ADC),fractional-order calculus(FROC),and continuous-time random-walk(CTRW)models,and used for radiomic feature extraction.Univariate Cox regression and least absolute shrinkage and selection operator(LASSO)-Cox regression were used to construct a radiomics score(Rad-score)for each of the three models.Patients were divided into high-and low-risk groups according to the median Rad-score(45 patients in each group).Predictive performance was evaluated using the concordance index(C-index)and time-dependent receiver operating characteristic(ROC)curves;the area under the curve(AUC)was calculated,and differences in AUC among the Rad-scores were compared using the DeLong test.Survival analysis was performed using the Kaplan-Meier method,and between-group differences were assessed using the log-rank test.Univariate and multivariable Cox regression analyses were used to identify independent prognostic factors.Results LASSO-Cox regression selected 2,3,and 3 features to construct the Rad-scores for the Mono-ADC,FROC,and CTRW models,respectively.The C-index of the Rad-score_CTRW model was 0.785,higher than those of the Rad-score_FROC model(0.735)and the Rad-score_ADC model(0.681).For predicting 3-year survival,the AUC of the Rad-score_CTRW model was 0.761,higher than those of the Rad-score_FROC model(0.703;Z=2.07,P=0.038)and the Rad-score_ADC model(0.652;Z=3.65,P<0.001).Only risk stratification based on the Rad-score_CTRW model significantly differentiated OS between the high-and low-risk groups(P=0.001).Multivariable Cox regression analysis showed that all three Rad-scores were independent predictors of OS.Conclusion Radiomic features derived from the CTRW model showed better performance in predicting OS in patients with ESCC than those derived from the FROC and Mono-ADC models.