Surgical endoscopy · 2026
Real-time surgical navigation for intraoperative lymph node localization during targeted robot-assisted pelvic and retroperitoneal lymph node dissection.
СтатьяНазвание и аннотация: Перевод в очереди
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Hiep Marijn A J, Heerink Wouter J, Groen Harald C, Venix Lisanne P J, Aguilera Saiz Laura, Kerkhof Enzo, van der Poel Henk G, van Leeuwen Pim J, van de Kamp Maaike W, Tummers Quirijn R J G, Ruers Theo J M
Аннотация
BACKGROUND: Localization of suspected metastatic LNs during targeted robot-assisted lymphadenectomy is challenging due to anatomical variability and surrounding vital structures. Image-guided surgical navigation may improve intraoperative LN localization and completeness of oncologic dissection. The aim of this study is to evaluate the accuracy and usability of surgical navigation for localization of suspected metastatic lymph nodes (LNs) during robot-assisted pelvic and retroperitoneal LN dissection.
METHODS: Patients with one or more suspected metastatic LNs on preoperative imaging scheduled for robot-assisted pelvic or retroperitoneal LN dissection were prospectively included. A patient-specific three-dimensional (3D) model was automatically registered intraoperatively using electromagnetically tracked ultrasound of the bone surface. Real-time navigation was displayed via the da Vinci® TilePro™ as a 3D model or augmented reality overlay. A tracked pointer or instrument was used for LN localization. Accuracy was defined as the shortest distance between the surgeon-indicated LN and the corresponding 3D model. Usability was assessed using the system usability scale (SUS).
RESULTS: Twenty patients with 40 target LNs were included. One para-aortic LN was inaccessible in a patient with a BMI of 52 kg/m2. The remaining 39 LNs were successfully localized using navigation with a median accuracy of 0.8 mm (IQR 0.0-3.0). Navigation supported surgical decision-making and LN localization, with a SUS score of 70 (IQR 64-73). Registration time was 7 (5-10) min. No navigation-related complications occurred.
CONCLUSIONS: Surgical navigation enabled highly accurate LN localization during robot-assisted pelvic and retroperitoneal LN dissection. The technique is safe, feasible, and supports targeted oncologic surgery and intraoperative decision-making. In the future, wireless tracking systems or simultaneous localization and mapping techniques could allow broader clinical implementation of the navigation technique.
METHODS: Patients with one or more suspected metastatic LNs on preoperative imaging scheduled for robot-assisted pelvic or retroperitoneal LN dissection were prospectively included. A patient-specific three-dimensional (3D) model was automatically registered intraoperatively using electromagnetically tracked ultrasound of the bone surface. Real-time navigation was displayed via the da Vinci® TilePro™ as a 3D model or augmented reality overlay. A tracked pointer or instrument was used for LN localization. Accuracy was defined as the shortest distance between the surgeon-indicated LN and the corresponding 3D model. Usability was assessed using the system usability scale (SUS).
RESULTS: Twenty patients with 40 target LNs were included. One para-aortic LN was inaccessible in a patient with a BMI of 52 kg/m2. The remaining 39 LNs were successfully localized using navigation with a median accuracy of 0.8 mm (IQR 0.0-3.0). Navigation supported surgical decision-making and LN localization, with a SUS score of 70 (IQR 64-73). Registration time was 7 (5-10) min. No navigation-related complications occurred.
CONCLUSIONS: Surgical navigation enabled highly accurate LN localization during robot-assisted pelvic and retroperitoneal LN dissection. The technique is safe, feasible, and supports targeted oncologic surgery and intraoperative decision-making. In the future, wireless tracking systems or simultaneous localization and mapping techniques could allow broader clinical implementation of the navigation technique.