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作 者:周理乾[1] 马少君[1] 樊国峰[1] 樊民义[1] ZHOU Liqian;MA Shaojun;FAN Guofeng;FAN Minyi(Department of Radiology,Shaanxi Provincial People’s Hospital,Xi’an 710068,China)
出 处:《陕西医学杂志》2021年第7期802-806,810,共6页Shaanxi Medical Journal
摘 要:目的:评估第二版前列腺影像报告和数据系统(PI-RADS v2)联合表观扩散系数(ADC)或ADC分类对前列腺癌(PCa)的诊断价值。方法:回顾分析前列腺特异抗原(PSA)异常患者329例,所有病例均先行3.0 T多参数磁共振成像(mpMRI)检查,再行经直肠超声引导下前列腺穿刺。以穿刺病理作为金标准,使用Logistic回归对PI-RADS v2评分联合ADC值或分类进行分析,运用受试者工作特征(ROC)比较PI-RADS v2评分联合ADC值或分类与单独PI-RADS v2评分、ADC值或分类曲线下面积(AUC)。结果:纳入病灶394个,经穿刺病理证实为194个PCa病灶和200个良性病灶。Logistic回归分析显示PI-RADS v2评分、ADC值或分类均为PCa的独立预测指标(均P<0.01)。PI-RADS v2评分+ADC值与PI-RADS v2评分+ADC分类AUC值比较差异无统计学意义(P>0.05),但均高于单独PI-RADS v2评分(均P<0.05)。对于外周带和移行带病灶亦如此(均P<0.05)。PI-RADS v2评分+ADC分类在PI-RADS v2评分为4分时AUC值最大。PI-RADS v2评分+ADC分类的部分ROC曲线下面积(pAUC)为单独PI-RADS v2评分的3倍。结论:ADC能明显提高PI-RADS v2评分对PCa的预测效能,尤其对PI-RADS v2评分为4分的病灶。Objective:To evaluate the efficiency of PI-RADS v2 in combination with ADC in the diagnosis of prostate cancer(PCa).Methods:A retrospective analysis of 329 patients with abnormal PSA was performed.All cases underwent 3.0 T multi-parameter magnetic resonance imaging(mpMRI)examination,followed by transrectal ultrasound-guided prostate puncture.With puncture pathology as the gold standard,Logistic regression was used to analyze the PI-RADS v2 score combined with ADC value or classification,and the receiver operating characteristic(ROC)was used to compare the AUC of PI-RADS v2 score combined with ADC value or classification with the AUC of PI-RADS v2 score,ADC value or classification alone.Results:394 lesions were included,and 194 PCa lesions and 200 benign lesions were confirmed by puncture pathology.Logistic regression analysis showed that PI-RADS v2 score,ADC value or classification were independent predictors of PCa(all P<0.01).There was no significant difference in AUC value between PI-RADS v2 score+ADC value and PI-RADS v2 score+ADC classification(P>0.05),but both were all higher than that of PI-RADS v2 score alone(all P<0.05).The same is true for the peripheral zone and transition zone lesions(all P<0.05).The PI-RADS v2 score+ADC classification has the highest AUC value when the PI-RADS v2 score was 4.The pAUC of the PI-RADS v2 score+ADC classification was 3 times that of the PI-RADS v2 score alone.Conclusion:ADC can significantly improve the predictive performance of PI-RADS v2 score for PCa,especially for lesions with PI-RADS v2 score of 4.
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