前列腺影像报告和数据系统2.1版联合临床指标对前列腺癌的诊断价值  

Diagnosis of Combining Prostate Imaging Reporting and Data System Version 2.1 with ClinicalIndicators in Prostate Cancer

作　　者：魏晓婷 钟淑媛 胡根文 邹锦森 丁志广 徐坚民[1] WEI Xiaoting;ZHONG Shuyuan;HU Genwen;ZOU Jinsen;DING Zhiguang;XU Jianmin(Department of Radiology,the Second Clinical Medical College of Jinan University,Shenzhen People's Hospital,Shenzhen 518000,China)

机构地区：[1]暨南大学第二临床医学院,深圳市人民医院放射科,广东深圳518000

出　　处：《中国医学影像学杂志》2021年第4期390-394,共5页Chinese Journal of Medical Imaging

基　　金：深圳市科技计划基础研究项目(JCYJ20180228164641207)。

摘　　要：目的探讨前列腺影像报告和数据系统(PI-RADS)2.1版对前列腺癌(PCa)的诊断效能,结合PI-RADS v2.1及前列腺特异性抗原(PSA)衍生指标,评价其对PCa阳性穿刺结果的预测效能。资料与方法收集行MRI检查并行首次前列腺穿刺活检术的180例患者,其中良性前列腺增生(BPH)111例,PCa 69例,包括临床有意义的前列腺癌(CsPCa)57例。所有患者均进行PI-RADS v2.1评分,同时收集患者年龄、PSA、游离PSA/总PSA(f PSA/tPSA),并计算PSA密度(PSAD)。采用单因素分析各指标在BPH组与PCa组间及非Cs PCa组与CsPCa组间的差异,绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评价各参数对PCa的诊断效能;采用二元Logistic回归分析PI-RADS v2.1联合临床指标对PCa的预测价值。结果PIRADS v2.1评分、PSA、f PSA/tPSA、PSAD及前列腺体积在BPH组与PCa组间及非CsPCa组与CsPCa组间差异均有统计学意义(P均<0.05),且PI-RADS v2.1评分对PCa的诊断效能最高,AUC为0.882(P<0.01);Logistic回归分析显示,PI-RADS v2.1评分及PSAD分层是PCa的独立预测因子,回归模型的AUC为0.897(P<0.01);当PI-RADS≤2分且PSAD≤0.350 ng/ml^(2)及PIRADS=3分且PSAD≤0.150 ng/ml^(2)时,CsPCa阳性率为0。结论PI-RADS v2.1评分结合PSAD有助于提高PCa的诊断效能,辅助指导临床穿刺决策。当患者PI-RADS≤2分且PSAD≤0.350 ng/ml~2或PI-RADS=3分且PSAD≤0.150 ng/ml^(2)时,不提示CsPCa。Purpose To investigate the value of prostate imaging reporting and data system version 2.1(PI-RADS v2.1)for diagnosing prostate cancer(PCa),and to evaluate the predictive value of PCa positive biopsy result combined with PI-RADS v2.1 and prostate-specific antigen derived indicators.Materials and Methods 180 patients underwent prostate puncture biopsy were enrolled,including 111 cases of benign prostatic hyperplasia(BPH)and 69 cases of PCa,57 cases were clinically significant prostate cancer(CsPCa)among them.PI-RADS v2.1 was used to describe the MRI findings.The age,PSA and free PSA/total PSA(fPSA/tPSA)of patients were collected,and calculated prostate-specific antigen density(PSAD).Univariate analysis was performed to analyze the statistically significant indicators.The area under ROC curve(AUC)was calculated to evaluate the diagnostic efficacy for PCa.Logistic regression was used to analyze the predictive value of PI-RADS v2.1 combined with clinical indicators for PCa.Results The differences of PI-RADS v2.1 score,PSA,fPSA/tPSA,PSAD and prostate volume between BPH group and PCa group,non-CsPCa group and CsPCa group were statistically significant(P<0.05).PI-RADS v2.1 had the highest diagnostic efficacy for PCa with AUC of 0.882(P<0.01).Logistic regression analysis revealed that PI-RADS v2.1 score and PSAD were independent predictors of PCa,and the AUC of the regression model was 0.897(P<0.01).Combining PI-RADS v2.1 score and PSAD,when PI-RADS v2.1 score≤2 and PSAD≤0.350 ng/ml^(2),or PI-RADS v2.1 score was 3 and PSAD≤0.150 ng/ml^(2),the CsPCa detection rate was 0.Conclusion Combining the PIRADS v2.1 and PSAD improve the diagnostic value of PCa,and assist in clinical biopsy decision-making.Patients with PI-RADS v2.1 score≤2 and PSAD≤0.350 ng/ml^(2),or PI-RADS v2.1 score of 3 and PSAD≤0.150 ng/ml^(2) might avoid unnecessary biopsies.

关 键 词：前列腺肿瘤 磁共振成像 前列腺影像报告和数据系统 前列腺特异性抗原 病理学 外科 诊断 鉴别 

分 类 号：R737.25[医药卫生—肿瘤] R730.42[医药卫生—临床医学]