| Literature DB >> 30830571 |
Luca Morelli1,2, Simone Guadagni3, Gregorio Di Franco3, Matteo Palmeri3, Niccolò Furbetta3, Desirée Gianardi3, Matteo Bianchini3, Andrea Moglia4, Giulio Di Candio3, Mauro Ferrari4,5, Raffaella Berchiolli4,5.
Abstract
Type II endoleak (T2E) represents a frequent and often challenging complication of endovascular aneurysm repair (EVAR). Endovascular treatment is the standard and most used strategy, but the recurrence after it remains high, especially due to lumbar arteries (LA) and inferior mesenteric artery (IMA) feeding. While conventional laparoscopy has been considered as an emerging method, robotic surgery is not reported yet for this indication. We herein describe our technique of minimally invasive T2E repair using a full robotic approach with the da Vinci Xi, reporting our preliminary experience with the first two patients who underwent this operation at our Institution. The procedure comprises two phases. The first phase consists of IMA ligation, left colon mobilization and infra-renal exposure of the anterior longitudinal ligament of the column and of the left side of the sac. The second phase entails the posterior aneurysm mobilization and the selective clipping of LA responsible of the T2E, as identified by the pre-operative CT scan. No intra-operative complications occurred and the average length of surgery was 183 min. The average length of hospitalization was 2.5 days. Robotic T2E repair can be considered a safe procedure and the da Vinci Xi, thanks to its increased dexterity and flexibility, allows to easily perform this multi-target operation (IMA and LA). The articulated instruments with motion scaling and tremor filtering facilitate a gently vascular dissection and an easy IMA and LA identification, dissection, and ligation. The TilePro function permits the operator to control from the console, with intra-operative color-Doppler ultrasound, the absence of residual endoleaks.Entities:
Keywords: Abdominal aortic aneurysms; Da Vinci Xi; Endoleak; Robotic repair
Mesh:
Year: 2019 PMID: 30830571 DOI: 10.1007/s11701-019-00944-z
Source DB: PubMed Journal: J Robot Surg ISSN: 1863-2483