The Predictive Value of Computed Tomography and HA3D Nephrometry Scores for Complications After Partial Nephrectomy: A Prospective Pilot Study

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Background/Objectives: Accurate preoperative assessment of renal tumor complexity is essential for surgical planning and for predicting perioperative outcomes after partial nephrectomy (PN). RENAL and PADUA nephrometry scores, traditionally derived from two-dimensional (2D) computed tomography (CT) imaging, are widely used to quantify renal tumor complexity and surgical risk. However, the introduction of hyperaccuracy three-dimensional (HA3D) models has enabled enhanced anatomical visualization, potentially improving the assessment of surgical difficulty and the prediction of postoperative complications. The aim of this study was to compare conventional CT-based RENAL and PADUA scores with HA3D-derived nephrometry scores in predicting perioperative complications in patients undergoing robot-assisted or laparoscopic PN. Methods: A total of 17 consecutive patients with intermediate- or high-complexity category renal tumors (RENAL ≥ 7) and moderate- or high-risk category tumors (PADUA ≥ 8) were prospectively enrolled. Preoperative demographic and clinical parameters, as well as intraoperative and postoperative data, were prospectively collected. Tumor characteristics were evaluated using both CT-based RENAL and PADUA scoring systems and HA3D nephrometry reconstruction. Associations between nephrometry scores and perioperative outcomes were assessed using Spearman’s correlation. Predictive performance for postoperative complications and early chronic kidney disease (CKD) was evaluated using receiver operating characteristic (ROC) analysis. Results: Overall, 41% and 35% of cases were downgraded according to three-dimensional (3D) RENAL and PADUA complexity–risk category assessment, respectively. Operative time demonstrated a moderate correlation with 3D RENAL (ρ = 0.57) and 3D PADUA (ρ = 0.49) scores. ROC curve analysis demonstrated numerical differences in area under the curve (AUC) values between 3D- and 2D-based nephrometry scores in predicting overall complications (RENAL: 0.61 vs. 0.54; PADUA: 0.69 vs. 0.46). 3D RENAL score demonstrated numerically higher AUC values for early postoperative CKD compared with 2D RENAL score (AUC: 0.72 vs. 0.67). Conclusions: HA3D-based nephrometry scores were associated with enhanced anatomical visualization, frequent downgrading of tumor complexity–risk categories, and numerical differences in predictive performance for postoperative complications and early renal functional decline compared with conventional CT-based scores. These findings suggest a potential role for HA3D modeling in preoperative planning for PN. However, given the limited sample size, these observations should be interpreted as exploratory and hypothesis-generating, and warrant validation in larger multicenter cohorts.

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