Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, 518035, China.
Department of Ultrasonography, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, 518035, China.
Abdom Radiol (NY). 2021 Jul;46(7):3410-3417. doi: 10.1007/s00261-021-03023-w. Epub 2021 Mar 12.
To determine the incidence and false-positive rates of clinically significant prostate cancer (CSPC) in prostate imaging reporting and data system (PI-RADS) category 4 and 5 lesions using PI-RADS v2.1.
One hundred and eighty-two lesions in 169 subjects with a PI-RADS score of 4 or 5 were included in our study. Lesions with clinically insignificant prostate cancer (CIPC) or benign pathologic findings were reviewed and categorized by a radiologist. The initial comparison of demographic and clinical data was performed by t-test and χ test, and then the logistic regression model was used to determine factors associated with CIPC or benign pathological findings.
Of the 182 PI-RADS category 4 and 5 lesions, 84.6% (154/182) were prostate cancer (PCa), 73.1% (133/182) were CSPC, and 26.9% (49/182) were CIPC or benign pathologic findings. The false-positive cases included 44.9% (22/49) with inflammation, 42.9% (21/49) with CIPC, 8.2% (4/49) with BPH nodules and 4.1% (2/49) with normal anatomy cases. In multivariate analysis, factors associated with CIPC or benign features included those in both the peripheral zone (PZ) and central gland (CG) (odds ratio [OR] 0.062; p = 0.003) and a low prostate-specific antigen density (PSAD) (OR 0.34; p = 0.012).
The integration of clinical information (PSAD and lesion location) into mpMRI to identify lesions helps with obtaining a clinically significant diagnosis and decision-making.
使用 PI-RADS v2.1 确定 PI-RADS 类别 4 和 5 病变中临床显著前列腺癌（CSPC）的发生率和假阳性率。
我们的研究纳入了 169 名患者的 182 个 PI-RADS 评分 4 或 5 的病变。由放射科医生对具有临床意义不显著前列腺癌（CIPC）或良性病理发现的病变进行回顾和分类。通过 t 检验和 χ 检验进行初始的人口统计学和临床数据比较，然后使用逻辑回归模型确定与 CIPC 或良性病理发现相关的因素。
在 182 个 PI-RADS 类别 4 和 5 病变中，84.6%（154/182）为前列腺癌（PCa），73.1%（133/182）为 CSPC，26.9%（49/182）为 CIPC 或良性病理发现。假阳性病例包括 44.9%（22/49）炎症，42.9%（21/49）CIPC，8.2%（4/49）BPH 结节和 4.1%（2/49）正常解剖病例。多变量分析表明，与 CIPC 或良性特征相关的因素包括外周带（PZ）和中央腺体（CG）（比值比 [OR] 0.062；p=0.003）和低前列腺特异性抗原密度（PSAD）（OR 0.34；p=0.012）。
将临床信息（PSAD 和病变位置）整合到 mpMRI 中有助于识别病变，从而获得有临床意义的诊断和决策。
