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

Abstract

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: V_T (volume of the tumor); V_T/V_K (ratio between tumor volume and kidney volume); CSA_3D (ie, contact surface area); UCS_3D (contact to the urinary collecting system); Tumor-Artery_3D: tumor's blood supply by tertiary segmental arteries (score = 1), secondary segmental artery (score = 2), or primary segmental/main renal artery (scoren = 3); S_T (tumor's sphericity); Conv_T (tumor's convexity); and Endophyticity_3D (ratio between the CSA_3D 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 (UCS_3D = 2), tumor with blood supply by primary or secondary segmentary arteries (Tumor-Artery_3D = 1 and 2), and high Endophyticity_3D values had significantly higher rates of overall complications (all p ≤ 0.03). At univariate analysis, UCS_3D, Tumor-Artery_3D, and Endophyticity_3D are significantly associated with overall complications; CSA_3D and Endophyticity_3D were associated with warm ischemia time; and CSA_3D 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.

Keywords: Complications; Renal cancer; Robot-assisted partial nephrectomy; Three-dimensional modeling; Three-dimensional parameters.