Department of Urology, Barretos Cancer Hospital, Barretos, R. Antenor Duarte Vilela, 1331, Barretos, São Paulo, 14784-400, Brazil.
Department of Urology, Base Hospital of Federal District, Brasilia, Brazil.
Eur Radiol. 2020 Sep;30(9):5004-5010. doi: 10.1007/s00330-020-06839-0. Epub 2020 Apr 19.
The objective of this study was to perform an independent external validation of the Giganti-Coppola nomogram (GCN), which uses clinical and radiological parameters to predict prostate extracapsular extension (ECE) on the final pathology of patients undergoing radical prostatectomy (RP).
Seventy-two patients diagnosed with prostate cancer (PCa), who were RP candidates from two institutions, were prospectively included. All patients underwent preoperative multi-parametric magnetic resonance imaging (mpMRI) at 1.5 T, without the use of an endorectal coil, with multiplanar images in T1WI, T2WI, DWI, and DCE. The AUC and a calibration graph were used to validate the nomogram, using the regression coefficients of the Giganti-Coppola study.
The original nomogram had an AUC of 0.90 (p = 0.001), with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 5.1%, 47.1%, 100%, and 48%, respectively. The calibration graph showed an overestimation of the nomogram for ECE.
The GCN has an adequate ability in predicting ECE; however, in our sample, it showed limited accuracy and overestimated likelihood of ECE in the final pathology of patients with PCa submitted to RP.
• Knowledge of preoperative local staging of prostate cancer is essential for surgical treatment. Extracapsular extension increases the chance of positive surgical margins. • Imaging modalities such as mpMRI alone does not have suitable accuracy in local staging. • Giganti-Coppola's nomogram achieved an adequate ability in predicting ECE.
本研究的目的是对 Giganti-Coppola 列线图(GCN)进行独立的外部验证,该列线图使用临床和影像学参数来预测接受根治性前列腺切除术(RP)的患者前列腺包膜外侵犯(ECE)的最终病理学结果。
前瞻性纳入了来自两个机构的 72 名被诊断为前列腺癌(PCa)且适合接受 RP 的患者。所有患者均在术前进行了 1.5T 多参数磁共振成像(mpMRI)检查,未使用直肠内线圈,采用 T1WI、T2WI、DWI 和 DCE 的多平面图像。使用 Giganti-Coppola 研究的回归系数,通过 AUC 和校准图来验证该列线图。
原始列线图的 AUC 为 0.90(p=0.001),灵敏度、特异性、阳性预测值、阴性预测值和准确性分别为 100%、5.1%、47.1%、100%和 48%。校准图显示 ECE 列线图存在高估。
GCN 具有预测 ECE 的良好能力;然而,在我们的样本中,它在预测接受 RP 的 PCa 患者的最终病理学中 ECE 的准确性有限,且高估了 ECE 的可能性。
了解前列腺癌术前局部分期对于手术治疗至关重要。包膜外侵犯增加了阳性手术切缘的可能性。
成像方式如 mpMRI 单独用于局部分期的准确性不足。
Giganti-Coppola 列线图在预测 ECE 方面具有良好的能力。