Robotic sentinel lymph node dissection for presumed early-stage epithelial ovarian cancer stadification by transperitoneal and retroperitoneal approaches.

Abstract

Introduction: Epithelial ovarian cancer (EOC) is a significant global health concern. Early detection remains rare, with only 20% of cases identified at an early stage, highlighting the critical need for effective staging interventions¹. Traditional extensive lymphadenectomy, associated with considerable morbidity, has led to the exploration of selective sentinel lymph node biopsy (SLNB), which is still under study ^1,2,3,4.

Methods: SLNB, enhanced by robotic technology, is demonstrated through two clinical case studies studies that show how robotic systems are used to meticulously identify and map sentinel nodes, focusing on procedural specifics and fluorescence-guided node identification. The article synthesizes insights from recent studies^1,2,3,4, emphasizing the integration of robotic technology with SLNB to enhance surgical precision, improve recovery, and reduce morbidity.

Discussion: We examine SLNB through retroperitoneal and transperitoneal approaches, highlighting technical aspects and the benefits of robotic assistance over conventional laparoscopy, such as improved precision and ergonomics. A recent analysis and meta-analysis¹ showed a high pooled detection rate, though the evidence quality is low. Recently, the MELISA³ and SELLY² studies were published, with MELISA showing higher detection, sensitivity, and specificity rates than SELLY. Sentinel lymph nodes vary in location, requiring meticulous exploration¹. The retroperitoneal approach might offer an advantage for para-aortic dissection, particularly in obese patients, however, in sentinel lymph node biopsy, the need for extensive dissection could potentially limit its use⁵. Key technique aspects include injection zones and using combined tracers². Limitations include variable detection rates, lack of standardized protocols, accessibility to robotic technology, and the need for advanced surgical skills¹.

Conclusion: SLNB, particularly with robotic assistance, shows promise for improving accuracy and reducing morbidity in epithelial ovarian cancer. However, its use remains limited to clinical trials. Future studies should focus on developing standardized protocols to achieve consistent results and provide sufficient evidence for its integration into routine clinical practice.