Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer.
Multiparametric Magnetic Resonance Imaging-based Prostate Specific Antigen Density and PI-RADSv2 score help identify Apical Prostate Cancer.
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DOI：
10.7150/jca.84278
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发表时间：
2023
影响因子：
3.9
通讯作者：
Zhou L
中科院分区：
文献类型：
--
作者：
Huang C;Rui R;Feng N;He Q;Gong Y;Li X;He S;Zhou L
目的：探讨术前多参数磁共振成像(MpMRI)在诊断侵袭性前列腺癌(APCA)中的作用，从而为患者的咨询和手术计划提供帮助。患者和方法：我们对2010年1月至2019年10月接受根治性前列腺切除术(RP)的662名患者进行了回顾性分析。所有患者均接受了术前前列腺活检和mpMRI检查。APCA定义为前列腺尖的任何恶性病变。检索临床、病理和mpMRI变量。进行单变量、多变量和受试者工作特性(ROC)分析。结果：共有214例(32.3%)患者存在APCA。表现为APCA的患者更有可能具有不良的临床病理特征(均P<；0.05)。在单变量分析中，血清前列腺特异性抗原(p<；0.001)、基于mpMRI的前列腺特异性抗原密度(p<；0.001)、前列腺影像报告和数据系统版本2(PI-RADSv2)评分(p<；0.001)、阳性核心数(p<；0.001)、阳性核心百分比(p<；0.001)、最大核心受累(p<；0.001)和活检GG(p=0.001)是APCa的显著预测因素。多变量分析显示，以mpMRI为基础的PSAD0.27 ng/ml/cm~3(优势比[OR]：2.251，p=0.003)、PI-≥评分和阳性核心率(OR：1.611，p=0.023)和阳性核心率(OR：2.333，p=0.041)是RP患者发生APCa的独立预测因素。基于mpMRI的PSAD和PI-RADSv2评分的AUC值分别为0.646(95%可信区间：0.608~0.682)和0.612(95%CI：0.568~0.656)。结论：术前基于mpMRI的PSAD和PI-RADSv2评分有助于确定APCA的存在，并可能有助于RP术中的手术决策。
Objective: To investigate the potential roles of preoperative multiparametric magnetic resonance imaging (mpMRI) in identifying aggressive apical prostate cancer (APCa), thereby helping to facilitate patient counseling and surgical planning. Patients and Methods: We performed a retrospective analysis of 662 patients who underwent radical prostatectomy (RP) between January 2010 to October 2019. All patients underwent a preoperative biopsy and mpMRI of the prostate. APCa was defined as any malignant lesions in the prostatic apex. Clinical, pathological and mpMRI variables were retrieved. Univariate, multivariate, and receiver operating characteristic (ROC) analyses were performed. Results: A total of 214 (32.3%) patients had APCa. Patients presenting APCa were more likely to harbor adverse clinicopathological features (all p < 0.05). On univariable analysis, serum prostate-specific antigen (PSA) (p < 0.001), mpMRI-based PSA density (PSAD) (p < 0.001), Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score (p < 0.001), number of positive cores (p < 0.001), percentage of positive cores (p < 0.001), max core involvement (p < 0.001) and biopsy GG (p = 0.001) were significant predictors of APCa. On multivariable analysis, mpMRI-based PSAD ≥ 0.27 ng/ml/cm3 (odds ratio [OR]: 2.251, p = 0.003), PI-RADSv2 score > 4 (OR: 1.611, p = 0.023) and percentage of positive cores (OR: 2.333, p = 0.041) were independently predictive of APCa during RP. The AUC values of mpMRI-based PSAD and PI-RADSv2 score were 0.646 (95% Confidence Intervals [CI]: 0.608-0.682) and 0.612 (95% CI: 0.568-0.656), respectively. Conclusion: Preoperative mpMRI-based PSAD and PI-RADSv2 score help identify the presence of APCa and may be useful for surgical decision-making during RP.
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