Abstract
Background: Isolated parenchymal splenic relapse is a rare condition experienced by patients presenting with recurrent ovarian cancer (ROC).1–3, 2 In such cases, complete secondary cytoreductive surgery (SCS) followed by chemotherapy offers significant overall survival benefits for platinum-sensitive ROC patients. Randomized trials such as DESKTOP-3 and SOC-1 described splenectomy during SCS in 6–15% of patients.4,5 Robotic-assisted surgery (RAS) and advanced three-dimensional (3D) imaging reconstruction can be integrated when choosing minimally invasive surgery (MIS) to reduce the risks associated with splenic procedures.6–8, 7 Methodology: The case of a 70-year-old BRCA2-mutated patient with single-site splenic ROC is presented. Computed tomography (CT) scan was reviewed by an expert radiologist during a multidisciplinary tumor board. The images were manually segmented using 3D Slicer software to obtain the final 3D reconstruction.9 Using the da Vinci Xi™ robot (Intuitive Surgical, Sunnyvale, CA, USA), a medial-to-lateral spleen dissection was performed. Several key surgical steps were followed to avoid tumor manipulation and subsequently minimize potential neoplastic spread. Results: Intraoperative ultrasound confirmed lesion localization, and advanced robotic instruments facilitated precise hilum control, reducing the risk of bleeding and pancreatic tail injury. Robotic SCS with complete tumor resection was achieved. No intraoperative or postoperative complications were reported. Final histology confirmed the diagnosis of high-grade ROC. Conclusion: RAS represents a viable option for SCS in ROC patients with isolated parenchymal localization. The integration of 3D reconstruction with RAS allows for a tailored approach in complex cases. A high-level of expertise and appropriate identification of candidates for MIS-SCS are required to achieve the best outcomes for ROC patients.
| Original language | English |
|---|---|
| Pages (from-to) | 4324-4325 |
| Number of pages | 2 |
| Journal | Annals of Surgical Oncology |
| Volume | 32 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 5 Gender Equality
All Science Journal Classification (ASJC) codes
- Surgery
- Oncology
Keywords
- Robotic surgery
- ovarian cancer
- recurrent ovarian cancer
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