Amparore Daniele, Piramide Federico, Verri Paolo, Checcucci Enrico, Piana Alberto, Basile Giuseppe, Larcher Alessandro, Gallioli Andrea, Territo Angelo, Gaya Josep Maria, Piazza Pietro, Puliatti Stefano, Grosso Antonio Andrea, Mari Andrea, Campi Riccardo, Zuluaga Laura, Burak Ucpinar, Ketan Badani, Serni Sergio, Capitanio Umberto, Montorsi Francesco, Mottrie Alexandre, Fiori Cristian, Minervini Andrea, Wiklund Peter, Breda Alberto, Porpiglia Francesco
Department of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, Italy.
Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, Candiolo, Italy.
Eur Urol Open Sci. 2025 Feb 21;74:11-20. doi: 10.1016/j.euros.2025.02.001. eCollection 2025 Apr.
The aim of our study was to compare assessment of PADUA and RENAL nephrometry scores and risk/complexity categories via two-dimensional (2D) imaging and three-dimensional virtual models (3DVM) in a large multi-institutional cohort of renal masses suitable for robot-assisted partial nephrectomy (RAPN), and evaluate the predictive role of these imaging approaches for postoperative complications.
Patients were prospectively enrolled from six international high-volume robotic centers, calculating PADUA and RENAL-nephrometry scores and their relative categories with 2D-imaging and 3DVMs. The concordance of nephrometry scores and categories between the two approaches was evaluated using χ tests and Cohen's κ coefficient. Receiver operating characteristic curves were plotted to assess the sensitivity and specificity of the 3DVM and 2D approaches for predicting the occurrence of postoperative complications. Multivariable logistic analyses were conducted to identify predictors of major postoperative complications.
A total of 318 patients were included in the study. There was low concordance for nephrometry scores and categories between the 3DVM and 2D assessment methods, with downgrading of PADUA and RENAL scores on 3DVM assessment in 43% and 49% of cases, and downgrading of the corresponding categories in 25% and 26%, respectively. Moreover, 3DVM assessment showed better accuracy than the 2D approach in predicting overall ( < 0.001) and major ( = 0.001) postoperative complications. In line with these findings, multivariable analyses showed that 3DVM-based nephrometry scores and categories were predictive of major postoperative complications ( < 0.001). Limitations include the risk of interobserver variability in evaluating nephrometry scores and categories, production costs for the 3DVMs, and the experience of the surgeons involved, with potential impacts on diffusion of this technology.
In this multi-institutional study, 3DVMs had superior accuracy to 2D images for evaluating the surgical complexity of renal masses and frequently led to downgrading. This could facilitate an increase in recommendations for kidney-sparing surgery and better identification of cases at risk of postoperative complications.
Our study shows that the use of three-dimensional models gives lower complexity scores for kidney tumors in comparison to standard two-dimensional scans. This can improve surgical planning and may boost the use of kidney-sparing techniques and better identification of cases that are more likely to have postoperative complications.
我们研究的目的是在一个适合机器人辅助部分肾切除术（RAPN）的大型多机构肾肿块队列中，通过二维（2D）成像和三维虚拟模型（3DVM）比较PADUA和RENAL肾计量评分及风险/复杂性分类评估，并评估这些成像方法对术后并发症的预测作用。
前瞻性纳入来自六个国际高容量机器人手术中心的患者，使用2D成像和3DVM计算PADUA和RENAL肾计量评分及其相对分类。使用χ检验和Cohen's κ系数评估两种方法之间肾计量评分和分类的一致性。绘制受试者工作特征曲线以评估3DVM和2D方法预测术后并发症发生的敏感性和特异性。进行多变量逻辑分析以确定术后主要并发症的预测因素。
本研究共纳入318例患者。3DVM和2D评估方法之间的肾计量评分和分类一致性较低，在3DVM评估中，43%的病例PADUA评分降低，49%的病例RENAL评分降低，相应分类降低的病例分别为25%和26%。此外，在预测总体（<0.001）和主要（=0.001）术后并发症方面，3DVM评估显示出比2D方法更高的准确性。与这些发现一致，多变量分析表明基于3DVM的肾计量评分和分类可预测术后主要并发症（<0.001）。局限性包括评估肾计量评分和分类时观察者间变异的风险、3DVM的生产成本以及参与手术的外科医生的经验，这些可能会对该技术的推广产生影响。
在这项多机构研究中，3DVM在评估肾肿块手术复杂性方面比2D图像具有更高的准确性，且经常导致评分降低。这可能有助于增加保肾手术的推荐，并更好地识别有术后并发症风险的病例。
我们的研究表明，与标准二维扫描相比，使用三维模型对肾肿瘤的复杂性评分更低。这可以改善手术规划，并可能促进保肾技术的应用，以及更好地识别更可能出现术后并发症的病例。
