A New Era in Perforator Flap Surgery for Breast Reconstruction: A Comparative Study of Robotic versus Standard Harvest of Bilateral Deep Inferior Epigastric Artery Perforator Flaps.

BACKGROUND:  Traditional deep inferior epigastric artery perforator (DIEP) flap harvest splits the anterior sheath, weakening the abdominal wall and predisposing patients to bulge or hernia. Abdominal wall morbidity may be decreased using minimally invasive techniques. We refined a transabdominal approach to the robotic harvest of bilateral DIEP flaps.

METHODS:  A retrospective medical record study involving all patients who underwent bilateral or bipedicled robotic DIEP (rDIEP) or standard DIEP (sDIEP) flap harvest between July 2021 and September 2022. Outcomes included abdominal wall morbidity, total operative time, length of stay (LOS), and complications.

RESULTS:  Forty-seven patients were included (48 sDIEP flaps, 46 rDIEP flaps) with no significant difference in patient characteristics. Fascial incision length in the rDIEP group was shorter (4.1 vs. 11.7 cm, p  < 0.001). Mesh reinforcement of the abdominal wall was used in 13/24 sDIEP and none in rDIEP patients ( p  < 0.001). Operative time was longer in the rDIEP cohort (739 vs. 630 minutes, p  = 0.013), although subanalysis showed no difference in the second half of the cohort. The average robotic dissection time was 135 minutes, which decreased significantly with the surgeon's experience. There were no intraoperative complications from using the robot. LOS was shorter with rDIEP but not statistically significant (3.9 vs. 4.3 days, p  = 0.157).

CONCLUSION:  This study represents the most extensive cohort analysis of bilateral rDIEP flap harvest, offering a comprehensive comparison to traditional sDIEP. The initial results underscore the viability of robotic techniques for flap harvesting, highlighting potential advantages including reduced fascial incision length and decreased abdominal disruption. Furthermore, using robotics may obviate the necessity for fascial reinforcement with mesh.