Novel Volumetric and Morphological Parameters Derived from Three-dimensional Virtual Modeling to Improve Comprehension of Tumor's Anatomy in Patients with Renal Cancer

Background: Three-dimensional (3D) models improve the comprehension of renal anatomy. Objective: To evaluate the impact of novel 3D-derived parameters, to predict surgical outcomes after robot-assisted partial nephrectomy (RAPN). Design, setting, and participants: Sixty-nine patients with cT1-T2 renal mass scheduled for RAPN were included. Three-dimensional virtual modeling was achieved from computed tomography. The following volumetric and morphological 3D parameters were calculated: VT (volume of the tumor); VT/VK (ratio between tumor volume and kidney volume); CSA3D (ie, contact surface area); UCS3D (contact to the urinary collecting system); Tumor-Artery3D: tumor's blood supply by tertiary segmental arteries (score = 1), secondary segmental artery (score = 2), or primary segmental/main renal artery (scoren = 3); ST (tumor's sphericity); ConvT (tumor's convexity); and Endophyticity3D (ratio between the CSA3D and the global tumor surface). Intervention: RAPN with a 3D model. Outcome measurements and statistical analysis: Three-dimensional parameters were compared between patients with and without complications. Univariate logistic regression was used to predict overall complications and type of clamping; linear regression was used to predict operative time, warm ischemia time, and estimated blood loss. Results and limitations: Overall, 11 (15%) individuals experienced overall complications (7.2% had Clavien ≥3 complications). Patients with urinary collecting system (UCS) involvement at 3D model (UCS3D = 2), tumor with blood supply by primary or secondary segmentary arteries (Tumor-Artery3D = 1 and 2), and high Endophyticity3D values had significantly higher rates of overall complications (all p ≤ 0.03). At univariate analysis, UCS3D, Tumor-Artery3D, and Endophyticity3D are significantly associated with overall complications; CSA3D and Endophyticity3D were associated with warm ischemia time; and CSA3D was associated with selective clamping (all p ≤ 0.03). Sample size and the lack of interobserver variability are the main limits. Conclusions: Three-dimensional modeling provides novel volumetric and morphological parameters to predict surgical outcomes after RAPN. Patient summary: Novel morphological and volumetric parameters can be derived from a three-dimensional model to describe surgical complexity of renal mass and to predict surgical outcomes after robot-assisted partial nephrectomy.