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前列腺影像报告和数据系统第 2 版是否足以发现具有临床意义的前列腺癌?基于每例病灶的影像学-病理学相关性研究。

Is Prostate Imaging Reporting and Data System Version 2 Sufficiently Discovering Clinically Significant Prostate Cancer? Per-Lesion Radiology-Pathology Correlation Study.

机构信息

1 Department of Radiology, Seoul Metropolitan Government, Seoul National University Boramae Medical Center, 20 Boramae-ro-5-Gil, Dongjak-Gu, Seoul 07061, Korea.

2 Department of Pathology, Seoul Metropolitan Government, Seoul National University Boramae Medical Center, Seoul, Korea.

出版信息

AJR Am J Roentgenol. 2018 Jul;211(1):114-120. doi: 10.2214/AJR.17.18684. Epub 2018 Apr 27.

Abstract

OBJECTIVE

The objective of our study was to evaluate the performance of multiparametric MRI with Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for detecting prostate cancer (PCA) and clinically significant PCA through this per-lesion one-to-one correlation study between pathologically proven lesions and MRI-visible lesions.

MATERIALS AND METHODS

A total of 93 PCA lesions from 44 patients who underwent radical prostatectomy were included in this retrospective study. Two radiologists scored every visible lesion with a PI-RADSv2 score of 3, 4, or 5 in each patient's multiparametric MRI examination using PI-RADSv2. A per-lesion one-to-one correlation between MRI-visible lesions and pathologically confirmed PCA lesions was conducted during regular radiology-pathology meetings at our center. The detection rates of clinically significant PCA and the proportions of clinically significant PCAs from MRI-visible and MRI-invisible PCAs were calculated. The performance of PI-RADSv2 for detecting clinically significant PCA was evaluated using the positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC) value.

RESULTS

Using a PI-RADSv2 score of 3, 4, or 5 as an MRI-visible lesion, 46.88% of clinically significant PCA lesions were detected. The PPV, NPV, and AUC were 96.77%, 45.16%, and 0.72, respectively. Tumor volume and secondary Gleason grade showed a statistically significant difference between MRI-visible and MRI-invisible clinically significant PCAs.

CONCLUSION

Multiparametric MRI with PI-RADSv2 missed a considerable number of clinically significant PCA lesions in this per-lesion analysis, causing a relatively low NPV and diagnostic performance compared with previous per-patient studies. However, the high PPV indicates that multiparametric MRI with PI-RADSv2 may be useful for follow-up of active surveillance and planning focal therapy.

摘要

目的

本研究的目的是通过对经病理证实的病变与 MRI 可见病变进行一对一的相关性研究,评估前列腺影像报告和数据系统第 2 版(PI-RADSv2)在多参数 MRI 检测前列腺癌(PCA)和临床显著 PCA 中的性能。

材料与方法

本回顾性研究共纳入 44 例接受根治性前列腺切除术的患者的 93 个 PCA 病变。两位放射科医生使用 PI-RADSv2 对每位患者的多参数 MRI 检查中的每个可见病变进行评分,PI-RADSv2 评分为 3、4 或 5。在我们中心的常规放射科-病理会议上,对 MRI 可见病变和经病理证实的 PCA 病变进行了病变对病变的相关性分析。计算了临床显著 PCA 的检出率以及 MRI 可见和 MRI 不可见 PCA 中临床显著 PCA 的比例。使用阳性预测值(PPV)、阴性预测值(NPV)和 ROC 曲线下面积(AUC)值评估 PI-RADSv2 检测临床显著 PCA 的性能。

结果

使用 PI-RADSv2 评分 3、4 或 5 作为 MRI 可见病变,可检出 46.88%的临床显著 PCA 病变。PPV、NPV 和 AUC 分别为 96.77%、45.16%和 0.72。MRI 可见和 MRI 不可见的临床显著 PCA 之间肿瘤体积和次要 Gleason 分级存在统计学差异。

结论

在本病变分析中,多参数 MRI 联合 PI-RADSv2 遗漏了相当数量的临床显著 PCA 病变,导致与之前的患者研究相比,NPV 和诊断性能相对较低。然而,高 PPV 表明,多参数 MRI 联合 PI-RADSv2 可能对主动监测和计划局部治疗的随访有用。

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