基于SWE和MRI对临床显著性前列腺癌的诊断价值

目的：探究基于剪切波弹性成像（SWE）和多参数磁共振成像（mpMRI）对临床显著性前列腺癌（csPCa）的诊断价值。方法：回顾性选取2020年10月至2022年1月在延安大学附属医院泌尿外科疑诊为前列腺癌（PCa）并行超声引导下前列腺穿刺活检的患者为研究对象，共纳入患者74例。根据穿刺活检病理结果将患者分为PCa组与非PCa组，csPCa组与非PCa+临床不显著前列腺癌组（cisPCa），其中PCa组24例，csPCa组17例。采用单因素及多因素logistic逐步回归分析筛选csPCa的独立预测因子，并通过ROC曲线比较预测概率值与各独立预测因子的诊断效能。结果：tPSA、fPSA、PSAD、PV、PIRADS、Emax差、Emean差和Emin差在PCa组与非PCa组，以及非PCa+cisPCa组与csPCa组之间的差异有统计学意义（P＜0.05）。logistic回归结果显示tPSA、PV、Emax差及PIRADS是csPCa的独立预测因子，ROC曲线结果显示logistic回归模型曲线下面积（AUC）为0.954，灵敏度为0.882，特异度为0.947，结果均优于各独立预测因子。结论：Emax差及PIRADS是csPCa的独立预测因子，与tPSA、PV联合具有较好的诊断效能。

Diagnostic Value of Clinically Significant Prostate Cancer Based on SWE and MRI

Objective: To explore the diagnostic value of shear wave elastography (SWE) and multi-parameters magnetic resonance imaging (mpMRI) in clinically significant prostate cancer (csPCa). Methods: From October 2020 to January 2022, patients suspected of prostate cancer (PCa) and underwent ultrasound-guided prostate biopsy were selected retrospectively for the study in the Department of Urology of the affiliated Hospital of Yan''an University. A total of 74 patients were enrolled. According to the pathological results of puncture biopsy, the patients were divided into PCa group and non-PCa group, csPCa group and non-PCa+ clinically insignificant adenocarcinoma group (cisPCa), including PCa group (n = 24) and csPCa group (n = 17). Univariate and multivariate logistic stepwise regression analysis was used to screen independent predictive factors of csPCa, and the diagnostic efficiency of the predictive probability value and each independent predictive factor were compared by ROC. Results: There were statistically significant differences between the PCa group and non-PCa group, csPCa group and non-PCa+ cisPCa group in tPSA, fPSA, PV, PSAD, PIRADS, Emax difference, Emean difference and Emin difference. Logistic regression results showed that tPSA, PV, Emax difference and PIRADS were independent predictive factors for csPCa. ROC results showed that the area under curve (AUC) of logistic regression model was 0.954, sensitivity was 0.882, specificity was 0.947, which were better than each independent predictive factor. Conclusion: Emax difference and PIRADS are independent predictive factors of csPCa, and combined with tPSA and PV has great diagnostic performance.