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.

中文翻译：

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复杂肿瘤 (PADUA ≥10) 情况下的三维增强现实机器人辅助肾部分切除术：一种克服超声引导的新术中工具。

背景

尽管机器人手术引入了技术改进，但复杂肿瘤的管理（PADUA 评分≥10）仍然是经腹膜机器人辅助肾部分切除术 (RAPN) 领域内的一个有争议的问题。

客观的

评估我们基于超精确模型 (HA3D) 的三维 (3D) 静态和弹性增强现实 (AR) 系统在经腹膜 RAPN (AR-RAPN) 期间识别肿瘤和肾内结构的准确性，与标准超声 (US) 相比.

设计、设置和参与者

进行了一项回顾性研究，包括 91 名接受 RAPN 治疗复杂肾肿瘤的患者，48 名接受 3D AR 指导，43 名接受 2D US 指导，时间为 2017 年 7 月至 2019 年 5 月。

手术程序

在接受 3D AR-RAPN 的患者中，虚拟图像重叠在切除和缝合阶段指导外科医生。在 2D US 组中，干预仅由 US 驱动。

测量

使用分类变量的 Fisher 精确检验和连续变量的 Mann-Whitney 检验来测试患者特征。收集术中、术后和手术结果。连续变量的所有结果都表示为中位数（范围），频率和比例报告为百分比。

结果和限制

使用 3D AR 引导可以通过相对于标准 2D US 引导更准确地 3D 感知不同结构的位置和性质来正确识别病变和实质内结构。这意味着整体缺血发生率较低（3D 组为 45.8%，美国组为 69.7%；p  = 0.03），摘除率较高（3D 和 US 组分别为 62.5% 和 37.5%；p  = 0.02)，以及较低的收集系统违规率（10.4% 对 45.5%；p  = 0.003）。术后，使用 3D AR 引导与 3D AR 组中手术相关并发症的低风险相关，并且在随访 3 个月时肾脏扫描时估计的肾血浆流量下降较低（3D 组中为 –12.38，而在 3D 组中为 –18.14美国集团；p  = 0.01）。本研究的主要局限性是随访时间短和样本量小。

结论

在复杂肿瘤的 AR-RAPN 期间重叠体内解剖结构的 HA3D 模型可用于识别仅用 US 难以可视化的病变和实质内结构。这意味着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。

患者总结

根据我们的研究结果，三维增强现实机器人辅助肾部分切除术似乎可以帮助外科医生治疗复杂的肾肿瘤，并具有潜在的术后早期益处。