Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
Eur Urol. 2020 Aug;78(2):229-238. doi: 10.1016/j.eururo.2019.11.024. Epub 2019 Dec 30.
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).
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.
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.
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.
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.
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.
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.
尽管机器人手术带来了技术上的进步，但在经腹腔机器人辅助部分肾切除术（RAPN）领域，对于复杂肿瘤（PADUA 评分≥10）的处理仍然存在争议。
评估我们基于高精度模型（HA3D）的三维（3D）静态和弹性增强现实（AR）系统在经腹腔 RAPN（AR-RAPN）中识别肿瘤和肾内结构的准确性，与标准超声（US）相比。
设计、地点和参与者：这是一项回顾性研究，纳入了 2017 年 7 月至 2019 年 5 月期间接受 RAPN 治疗的 91 例复杂肾肿瘤患者，其中 48 例采用 3D AR 引导，43 例采用 2D US 引导。
在接受 3D AR-RAPN 的患者中，虚拟图像重叠可在切除和缝合阶段指导外科医生。在 2D US 组中，仅通过 US 进行干预。
使用 Fisher 精确检验对分类变量和 Mann-Whitney 检验对连续变量进行患者特征测试。收集术中、术后和手术结果。所有连续变量的结果均表示为中位数（范围），并以百分比报告频率和比例。
使用 3D AR 引导可以更准确地识别病变和肾内结构，对不同结构的位置和性质有更准确的 3D 感知。这转化为较低的总缺血发生率（3D 组为 45.8%，US 组为 69.7%；p=0.03）、更高的剜除率（62.5%比 3D 组和 US 组分别为 37.5%；p=0.02）和较低的集合系统侵犯率（10.4%比 45.5%；p=0.003）。术后，3D AR 引导的使用与 3D AR 组中与手术相关的并发症风险较低相关，并且在 3 个月的随访时肾扫描估计的肾血浆流量下降较低（3D 组为-12.38，US 组为-18.14；p=0.01）。本研究的主要局限性是随访时间短和样本量小。
在 AR-RAPN 治疗复杂肿瘤时，与体内解剖结构重叠的 HA3D 模型可用于识别 US 难以可视化的病变和肾内结构。这转化为切除阶段质量的潜在改善和术后并发症的减少，以及更好的功能恢复。
根据我们的发现，三维增强现实机器人辅助部分肾切除术似乎有助于外科医生治疗复杂的肾肿瘤，并可能在术后早期获益。
