The predictive value of dynamic contrast-enhanced MRI quantitative analysis for perineural invasion in peripheral prostate cancer
10.3969/j.issn.1002-1671.2024.10.016
- VernacularTitle:动态对比增强MRI定量分析对外周带前列腺癌神经侵犯的预测价值
- Author:
Erpeng CAI
1
;
Kai TANG
;
Xiaofeng HU
;
Hu ZHANG
;
Xianfeng ZHU
;
Yan WANG
Author Information
1. 芜湖市第二人民医院影像科,安徽 芜湖 241000
- Keywords:
dynamic contrast-enhanced magnetic resonance imaging;
quantitative parameters;
prostate cancer;
perineural invasion
- From:
Journal of Practical Radiology
2024;40(10):1649-1652,1657
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of quantitative parameters(Kep and Ktrans)of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI),in predicting perineural invasion(PNI)in peripheral prostate cancer(PCa).Methods The clinical and preoperative MRI data of 45 patients with peripheral PCa who underwent radical prostatectomy(RP)were analyzed retrospectively.According to the pathological results,the patients were divided into PNI group(n=27)and non-PNI group(n=18).Various parameters,including age,total prostate specific antigen(tPSA),Ktrans value,Kep value,apparent diffusion coefficient(ADC)value,prostate volume,maximum lesion diameter,and prostate-specific antigen density(PSAD)were compared between the two groups.Multivariate logistic regression analysis was used to identify independent predictors of PNI,and a joint prediction model was established.The DeLong test was used to compare differences in the area under the curve(AUC)between the joint prediction model and each independent predictor.Results The univariate analysis identified statistically significant differences in the tPSA,Ktrans value,ADC value,maximum lesion diameter,and PSAD between the two groups(P＜0.01).The multivariate analysis showed that the Ktrans value and the maximum lesion diameter were independent predictors of PNI,with AUC of 0.854 and 0.874,respectively(P＜0.01).The AUC of the joint prediction model for PNI diagnosis was 0.955(P＜0.001).The DeLong test showed that the AUC of the joint prediction model for PNI diagnosis was better than that of the Ktrans and the maximum lesion diameter(P＜0.05).Conclusion The Ktrans value can be used to predict PNI.Furthermore,the combination of the Ktrans value and the maximum lesion diameter is more effective for predicting PNI than traditional methods.This provides more reference basis for the selection of clinical treatment methods.
