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. PATIENT SUMMARY: Based on our findings, three-dimensional augmented reality robot-assisted partial nephrectomy seems to help surgeons in the management of complex renal tumours, with potential early postoperative benefits.
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. PATIENT SUMMARY: Based on our findings, three-dimensional augmented reality robot-assisted partial nephrectomy seems to help surgeons in the management of complex renal tumours, with potential early postoperative benefits.
Authors: Clément Michiels; Zine-Eddine Khene; Thomas Prudhomme; Astrid Boulenger de Hauteclocque; François H Cornelis; Mélanie Percot; Hélène Simeon; Laure Dupitout; Henri Bensadoun; Grégoire Capon; Eric Alezra; Vincent Estrade; Franck Bladou; Grégoire Robert; Jean-Marie Ferriere; Nicolas Grenier; Nicolas Doumerc; Karim Bensalah; Jean-Christophe Bernhard Journal: World J Urol Date: 2021-04-02 Impact factor: 4.226
Authors: B M Zeeshan Hameed; Aiswarya V L S Dhavileswarapu; Syed Zahid Raza; Hadis Karimi; Harneet Singh Khanuja; Dasharathraj K Shetty; Sufyan Ibrahim; Milap J Shah; Nithesh Naik; Rahul Paul; Bhavan Prasad Rai; Bhaskar K Somani Journal: J Clin Med Date: 2021-04-26 Impact factor: 4.241
Authors: Naren Nimmagadda; James M Ferguson; Nicholas L Kavoussi; Bryn Pitt; Eric J Barth; Josephine Granna; Robert J Webster; S Duke Herrell Journal: World J Urol Date: 2021-06-16 Impact factor: 4.226
Authors: Nicholas L Kavoussi; Bryn Pitt; James M Ferguson; Josephine Granna; Andria Remirez; Naren Nimmagadda; Rachel Melnyk; Ahmed Ghazi; Eric J Barth; Robert J Webster; Stanley Duke Herrell Journal: J Endourol Date: 2020-11-11 Impact factor: 2.619