Application value of DCE-MRI and DWI in prognosis evaluation of patients with glioma

OUYANG Ningpeng; ZENG Hao; HE Changlin; YU Xiaoping

doi:10.19300/j.2025.L22023

Abstract：Objective To analyze the application value of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and diffusion-weighted imaging(DWI)in the prognostic evaluation of patients with glioma.Methods A total of 184 glioma patients confirmed by surgical resection or biopsy pathology were retrospectively selected.Based on postoperative follow-up survival time,patients were divided into a poor prognosis group(survival time＜24 months,n=64)and a good prognosis group(n=120).The general data,DCE-MRI parameters[volume transfer constant(Ktrans),extracellular space volume fraction(ve)],and DWI parameters[apparent diffusion coefficient(ADC),mean diffusion coefficient(MD)]were compared between the two groups using independent samples t test and Chi-square test.Univariate and multivariate Logistic regression were used to identify the prognostic factors predicting the prognosis of glioma patients,and a nomogram model was constructed accordingly.Receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to analyze the predictive value of each single factor and nomogram model.Calibration curve was used to evaluate the calibration of the model,and decision curve was used to evaluate the net benefit of the model.Results The proportion of patients undergoing partial tumor resection and the levels of Ktrans and ve were significantly higher in the poor prognosis group than in the good prognosis group(all P＜0.05).The proportion of patients receiving postoperative chemoradiotherapy and the levels of ADC and MD were significantly lower in the poor prognosis group than in the good prognosis group(all P＜0.05).Partial tumor resection,Ktrans,and ve were independent risk factors for the prognosis of glioma patients,while postoperative chemoradiotherapy,ADC,and MD were protective factors for the prognosis of glioma patients(all P＜0.05).A nomogram model was constructed by combining these six indicators.ROC curve analysis showed that the method of tumor resection,postoperative chemoradiotherapy,Ktrans,ve,ADC,MD,and the nomogram model could predict the prognosis of glioma patients.The nomogram model had the best prediction performance,with an AUC=0.829(95％CI:0.764-0.893).The calibration curve showed good consistency between the predicted probability and the actual probability of glioma patient prognosis.The decision curve analysis showed that the model achieved good clinical net benefit when the risk threshold interval was 37％to 88％.Conclusion DCE-MRI and DWI can be used to evaluate the prognosis of glioma patients.The nomogram model constructed based on clinical,DCE-MRI,and DWI factors has high clinical application value.