Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium; IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium; ORSI Academy, Melle, Belgium.
IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium.
Eur Urol. 2023 May;83(5):413-421. doi: 10.1016/j.eururo.2023.01.003. Epub 2023 Feb 1.
Selective clamping during robot-assisted partial nephrectomy (RAPN) requires extensive knowledge on patient-specific renal vasculature, obtained through imaging.
To validate an in-house developed perfusion zone algorithm that provides patient-specific three-dimensional (3D) renal perfusion information.
DESIGN, SETTING, AND PARTICIPANTS: Between October 2020 and June 2022, 25 patients undergoing RAPN at Ghent University Hospital were included. Three-dimensional models, based on preoperative computed tomography (CT) scans, showed the clamped artery's ischemic zone, as calculated by the algorithm.
All patients underwent selective clamping during RAPN. Indocyanine green (ICG) was administered to visualize the true ischemic zone perioperatively. Surgery was recorded for a postoperative analysis.
The true ischemic zone of the clamped artery was compared with the ischemic zone predicted by the algorithm through two metrics: (1) total ischemic zone overlap and (2) tumor ischemic zone overlap. Six urologists assessed metric 1; metric 2 was assessed objectively by the authors.
In 92% of the cases, the algorithm was sufficiently accurate to plan a selective clamping strategy. Metric 1 showed an average score of 4.28 out of 5. Metric 2 showed an average score of 4.14 out of 5. A first limitation is that ICG can be evaluated only at the kidney surface. A second limitation is that mainly patients with impaired renal function are expected to benefit from this technology, but contrast-enhanced CT is required at present.
The proposed new tool demonstrated high accuracy when planning selective clamping for RAPN. A follow-up prospective study is needed to determine the tool's clinical added value.
In partial nephrectomy, the surgeon has no information on which specific arterial branches perfuse the kidney tumor. We developed a surgeon support system that visualizes the perfusion zones of all arteries on a three-dimensional model and indicates the correct arteries to clamp. In this study, we validate this tool.
机器人辅助部分肾切除术（RAPN）中的选择性夹闭需要通过成像获得患者特定的肾血管知识。
验证一种内部开发的灌注区算法，该算法提供患者特定的三维（3D）肾灌注信息。
设计、设置和参与者：2020 年 10 月至 2022 年 6 月期间，在根特大学医院接受 RAPN 的 25 名患者被纳入本研究。基于术前计算机断层扫描（CT）扫描的 3D 模型显示了算法计算的夹闭动脉的缺血区。
所有患者均在 RAPN 中接受选择性夹闭。术中给予吲哚菁绿（ICG）以可视化手术期间的真实缺血区。术后对手术进行记录以进行分析。
通过两个指标比较夹闭动脉的真实缺血区与算法预测的缺血区：（1）总缺血区重叠和（2）肿瘤缺血区重叠。六位泌尿科医生评估了指标 1；作者客观评估了指标 2。
在 92%的情况下，算法足以准确规划选择性夹闭策略。指标 1 的平均得分为 5 分中的 4.28 分。指标 2 的平均得分为 5 分中的 4.14 分。第一个局限性是 ICG 只能在肾表面进行评估。第二个局限性是，预计只有肾功能受损的患者将从这项技术中受益，但目前需要进行增强 CT 检查。
当计划 RAPN 的选择性夹闭时，所提出的新工具表现出了高度的准确性。需要进行前瞻性研究以确定该工具的临床附加价值。
在部分肾切除术，外科医生无法获得哪些特定的动脉分支为肾脏肿瘤供血的信息。我们开发了一种外科医生支持系统，该系统可以在 3D 模型上可视化所有动脉的灌注区，并指示正确的动脉进行夹闭。在这项研究中，我们验证了该工具。
