探讨多模态超声联合应用在前列腺癌（PCa）诊断中的临床价值。

选取2017年7月至2018年12月在温州医科大学附属第一医院就诊的临床疑似前列腺癌的患者202例，所有患者均行实验室检查及经直肠多模态超声检查，根据手术病理结果分为前列腺癌组和非前列腺癌组，应用Logistic回归单因素及多因素分析分别建立多模态超声诊断前列腺癌的模型及多模态超声联合实验室检查和临床资料诊断前列腺癌的模型，应用受试者工作特征曲线（ROC）曲线下面积比较新建两个模型、实验室检查、临床资料对前列腺癌的诊断效能。

单因素Logistic回归分析结果显示二维超声、彩色多普勒、弹性成像、造影剂到达时间、峰值强度、强度差以及单位时间增强强度诊断前列腺癌，差异均有统计学意义（χ²=5.89、13.81、44.15，Z=1.55、2.16、2.81、2.43，P均<0.05），多因素Logistic回归分析结果显示：弹性成像和强度差是诊断前列腺癌的独立预测因子，建立模型多模态超声（MUS）评分。联合MUS评分、实验室检查和临床资料，进行单因素及多因素Logistic回归分析，结果显示，MUS评分、前列腺特异抗原密度（PSAD）和年龄是诊断前列腺癌的独立预测因子，建立模型MPA（MUS-PSAD-AGE）评分。MPA评分诊断PCa的ROC曲线下面积0.906，敏感度78.50%，特异度91.49%，阳性预测值91.30%，阴性预测值78.90%，MUS评分诊断PCa的ROC曲线下面积0.773，敏感度53.27%，特异度92.55%，阳性预测值89.10%，阴性预测值63.50%，PSAD诊断PCa的ROC曲线下面积0.847，敏感度76.64%，特异度89.36%，阳性预测值89.10%，阴性预测值77.10%，年龄诊断PCa的ROC曲线下面积0.675，敏感度77.57%，特异度48.94%，阳性预测值63.40%，阴性预测值65.70%。MPA评分对前列腺癌的诊断效能最高，且与MUS评分、PSAD及年龄比较，差异均有统计学意义（Z=8.48，t=-4.45，P均<0.05）。

多模态超声联合PSAD及年龄诊断前列腺癌具有较高的临床应用价值。

To evaluate the clinical value of multimodal ultrasound in the diagnosis of prostate cancer (PCa).

A total of 202 patients with clinically suspected prostate cancer from July 2017 to December 2018 were enrolled and underwent laboratory examinations and transrectal multimodal ultrasonography. According to the surgical pathological results, the patients were divided into either a PCa group or a non-PCa group. Univariate and multivariate logistic regression analyses were used to establish a model of multimodal ultrasonography for diagnosis of PCa and a model of multimodal ultrasonography combined with laboratory tests and clinical data for diagnosis of PCa. The area under the ROC curve was used to compare the diagnostic efficacy of the two new models, laboratory tests, and clinical data for PCa.

Univariate logistic regression analysis showed that two-dimensional ultrasound, color Doppler flow imaging, elastography, contrast agent arrival time, peak intensity, intensity difference, and unit time enhancement intensity were statistically significant in the diagnosis of PCa (χ²=5.89, 13.81, and 44.15; Z=1.55, 2.16, 2.81, and 2.43, respectively; P<0.05). Multivariate logistic regression analysis showed that elastography and intensity difference were independent predictors of PCa diagnosis. Then, a model of multimodal ultrasonography (MUS) score was established. MUS score, laboratory tests, and clinical data were combined to conduct univariate and multivariate logistic regression analyses, which that MUS score, prostate specific antigen density (PSAD), and age were independent predictors of PCa diagnosis. Then, a model of MPA (MUS-PSAD-AGE) score was established. The area under the ROC curve, sensitivity, specificity, positive predictive value, and negative predictive value of MPA score in diagnosing PCa were 0.906, 78.50%, 91.49%, 91.30%, and 78.90%; while those of MUS score, age, and PSAD were 0.773, 53.27%, 92.55%, 89.10%, and 63.50%; 0.847, 76.64%, 89.36%, 89.10%, and 77.10%; and 0.675, 77.57%, 48.94%, 63.40%, and 65.70%, respectively. MPA score is the most effective diagnostic indictor for PCa, which showed significantly higher diagnostic efficiency compared with MUS score, PSAD, and age (Z=8.48, t=-4.45, P<0.05).

Multimodal ultrasonography combined with PSAD and age have high clinical value in the diagnosis of PCa.