Abstract
BackgroundTo assess the impact of volumetry of perinephric fat (PNF) on the perioperative outcomes of robot-assisted partial nephrectomy (RAPN).MethodsBetween 2016 and 2019, a single surgeon performed RAPN for 128 patients with clinical T1a-b renal tumors at our institution, and the 70 most recent patients were included in this study to minimize the effects of surgical experience. PNF was defined as a fatty area around the kidney within the anatomical structures, including the lateroconal fascia, fusion fascia, psoas muscle, lumbar quadrate muscle and diaphragm, and its volume was calculated based on reconstructed three-dimensional computed tomography images using the SYNAPSE VINCENT system.ResultsIn this series, the trifecta and MIC (margin, ischemia and complications) score system outcomes were achieved in 69 (98.6%) and 64 patients (91.4%), respectively. The median PNF volume in the 70 patients was 166.05 cm3, which was significantly correlated with both the body mass index (BMI) and Mayo adhesive probability (MAP) score (correlation coefficient = 0.68 and 0.74, respectively). There was no significant difference in the R.E.N.A.L. nephrometry score, PNF volume or console time during RAPN among 5 groups consisting of 14 consecutive patients. Of several factors examined, the console time was significantly affected by the sex, MAP score and PNF volume, and only the PNF volume was independently associated with the console time.ConclusionEven if performed by an experienced robotic surgeon beyond the initial learning curve, the PNF volume may influence the console time during RAPN.
Highlights
To assess the impact of volumetry of perinephric fat (PNF) on the perioperative outcomes of robotassisted partial nephrectomy (RAPN)
Davidiuk et al advocated the Mayo adhesive probability (MAP) score in order to accurately predict the presence of adherent perinephric fat (APF) [15], and its usefulness was confirmed in several previous studies [16, 17]. This score is somewhat subjective regarding the definitions of both APF and the score itself, and is not intended to directly predict the surgical difficulty of Partial nephrectomy (PN). Considering these findings, we focused on the PNF volume, which may influence the complexity of RAPN, and conducted 3-dimensional (3D) volumetry for PNF on a total of 70 patients undergoing RAPN performed by a single experienced robotic surgeon in order to assess the impact of PNF volume on their perioperative outcomes
We hypothesized that the exact PNF volume can serve as a better predictor for the complexity of RAPN; this study was conducted to characterize the effects of the PNF volume on the perioperative outcomes in a total of 70 consecutive patients with clinical T1 renal tumors who underwent RAPN performed by a single experienced robotic surgeon beyond the initial learning curve
Summary
To assess the impact of volumetry of perinephric fat (PNF) on the perioperative outcomes of robotassisted partial nephrectomy (RAPN). Robot-assisted PN (RAPN) has become prevalent due to marked improvements of perioperative outcomes [2,3,4], with a shorter learning curve than laparoscopic PN [5, 6]. It is well known that the surgical complexity of RAPN varies depending on a wide variety of factors [7]. It is not uncommon to encounter cases in which it is difficult to perform RAPN even by experienced robotic surgeons. There are several image-based morphometry scoring systems that enable the quantification of relevant anatomical findings to help predict the potential complexity of PN, such as the R.E.N.A.L. nephrometry score, PADUA prediction score and centrality index (C-index)
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