Background
Despite technical improvements introduced with robotic surgery, management of complex tumours (PADUA score ≥10) is still a matter of debate within the field of transperitoneal robot-assisted partial nephrectomy (RAPN).
Objective
To evaluate the accuracy of our three-dimensional (3D) static and elastic augmented reality (AR) systems based on hyperaccuracy models (HA3D) in identifying tumours and intrarenal structures during transperitoneal RAPN (AR-RAPN), compared with standard ultrasound (US).
Design, setting, and participants: A retrospective study was conducted, including 91 patients who underwent RAPN for complex renal tumours, 48 with 3D AR guidance and 43 with 2D US guidance, from July 2017 to May 2019.
Surgical procedure
In patients who underwent 3D AR-RAPN, virtual image overlapping guided the surgeon during resection and suture phases. In the 2D US group, interventions were driven by US only.
Measurements
Patient characteristics were tested using the Fisher’s exact test for categorical variables and the Mann-Whitney test for continuous ones. Intraoperative, postoperative, and surgical outcomes were collected. All results for continuous variables were expressed as medians (range), and frequencies and proportions were reported as percentages.
Results and limitations
The use of 3D AR guidance makes it possible to correctly identify the lesion and intraparenchymal structures with a more accurate 3D perception of the location and the nature of the different structures relative to the standard 2D US guidance. This translates to a lower rate of global ischaemia (45.8% in the 3D group vs 69.7% in the US group; p = 0.03), higher rate of enucleation (62.5% vs 37.5% in the 3D and US groups, respectively; p = 0.02), and lower rate of collecting system violation (10.4% vs 45.5%; p = 0.003). Postoperatively, 3D AR guidance use correlates to a low risk of surgery-related complications in 3D AR groups and a lower drop in estimated renal plasma flow at renal scan at 3 mo of follow-up (-12.38 in the 3D group vs -18.14 in the US group; p = 0.01). The main limitations of this study are short follow-up time and small sample size.
Conclusions
HA3D models that overlap in vivo anatomy during AR-RAPN for complex tumours can be useful for identifying the lesion and intraparenchymal structures that are difficult to visualise with US only. This translates to a potential improvement in the quality of the resection phase and a reduction in postoperative complications, with better functional recovery.