前列腺影像报告和数据系统2.1版联合前列腺特异性抗原密度对特异性抗原灰区前列腺临床显著癌的诊断价值  

Diagnosis of Prostate Imaging Reporting and Data System Version 2.1 Combined with PSAD for Clinically Significant Prostate Cancer in the Gray Zone of Prostate-Specific Antigen

作　　者：张云[1,2] 董喆[1,2] 刘百川 赵建 王海屹[2] 叶慧义[2] ZHANG Yun;DONG Zhe;LIU Baichuan;ZHAO Jian;WANG Haiyi;YE Huiyi(Department of Radiology,the First Medical Center of Chinese PLA General Hospital,Beijing 100853,China;不详)

机构地区：[1]解放军总医院第六医学中心放射诊断科,北京100048 [2]解放军总医院第一医学中心放射诊断科,北京100853 [3]武警四川省总队医院医学影像科,四川乐山614000

出　　处：《中国医学影像学杂志》2024年第5期492-498,共7页Chinese Journal of Medical Imaging

基　　金：解放军总医院第六医学中心创新培育基金(CXPY202107)。

摘　　要：目的基于双中心数据,探讨前列腺影像报告和数据系统2.1版(PI-RADS v2.1)联合前列腺特异性抗原密度(PSAD)在前列腺特异性抗原(PSA)灰区(4~10 ng/ml)患者中对临床显著性前列腺癌(csPCa)的诊断价值。资料与方法回顾性分析2017年1月—2022年5月解放军总医院第一医学中心(中心一)和解放军总医院第六医学中心(中心二)行多参数磁共振成像且具备病理结果的PSA灰区前列腺疾病患者的临床及影像资料。将中心一患者作为训练组(220例),中心二患者作为测试组(50例)。训练组应用Logistic回归确定csPCa的独立预测因素,并分析多参数组合对csPCa的诊断效能,在测试组进行验证。结果训练组csPCa和非csPCa组前列腺体积、PSAD、PI-RADS v2.1评分差异有统计学意义(Z=-6.468、6.589、75.676,P均<0.001);Logistic回归分析显示PI-RADS v2.1评分和PSAD是csPCa的独立危险因素(P均<0.001)。训练组和测试组PI-RADS v2.1+PSAD组成的Logistic回归模型预测PSA灰区csPCa的曲线下面积为0.860(95%CI 0.808~0.903)、0.906(95%CI 0.790~0.970);Logistic回归模型的曲线下面积高于PI-RADS v2.1和PSAD,差异有统计学意义(P均<0.05)。当PI-RADS v2.1评分为低或中危组且PSAD<0.15 ng/ml^(2)时,训练组和测试组的csPCa检出率较低。结论PI-RADS v2.1评分和PSAD是预测PSA灰区csPCa的独立危险因素,两者联合应用对PSA灰区csPCa的诊断效能优于两者单独应用,有助于临床活检决策。Purpose To explore the diagnostic value of prostate imaging report and data system 2.1(PI-RADS v2.1)combined with prostate-specific antigen density(PSAD)for clinically significant prostate cancer(csPCa)in prostate-specific antigen(PSA)gray area(4-10 ng/ml)based on two-center data.Materials and Methods The clinical and imaging data of patients with PSA gray zone prostate disease who underwent multi-parametric magnetic resonance imaging and all pathological data in the First Medical Center(center 1)and the Sixth Medical Center(center 2)of the Chinese PLA General Hospital from January 2017 to May 2022 were retrospectively selected and analyzed.The patients from center 1 were used as the training group(220 cases),and the patients from center 2 were used as the test group(50 cases).Logistic regression was used to determine the independent predictors of csPCa in the training group,and the diagnostic efficacy of multi-parameter combination for csPCa was analyzed,which was further verified in the test group.Results There were significant differences in prostate volume,PSAD and PI-RADS v2.1 scores between the csPCa and non-csPCa groups in the training group(Z=-6.468,6.589,75.676,all P<0.001).Logistic regression analysis showed that PI-RADS v2.1 score and PSAD were the independent risk factors for csPCa(both P<0.001).The area under the curve of the Logistic regression model composed of PI-RADS v2.1 and PSAD for predicting csPCa in the PSA gray zone was 0.860(95%CI 0.808-0.903)in the training group and 0.906(95%CI 0.790-0.970)in the test group,respectively.The area under the curve of Logistic regression model was significantly higher than that of PI-RADS v2.1 and PSAD,respectively,with statistically significant difference(both P<0.05).When the PI-RADS v2.1 score was low or moderate risk and PSAD<0.15 ng/ml^(2),csPCa in the training group and the test group was with low detection rate.Conclusion PI-RADS v2.1 score and PSAD may be the independent risk factors for predicting csPCa in the PSA gray zone.The combined application

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 

分 类 号：R737.25[医药卫生—肿瘤] R445.2[医药卫生—临床医学]