Jason C C Kwok, Petko Shtarbanov, Mary Dowchan-Kowalska, Nianhe Luo, Thierry Schweizer, Pennylouise Hever, Stephen F. Hamilton, Shadi Ghali, Dariush Nikkhah
BACKGROUND: The deep inferior epigastric artery perforator (DIEP) flap remains the gold standard for autologous breast reconstruction. Traditional harvest techniques often require a large fascial incision that increases donor-site morbidity. Minimally-invasive approaches, such as robotic-assisted incisions, reduce this impact but introduce a steep learning curve and higher intra-operative costs. We aimed to detail our early experience in hand-performed minimal fascial incision (MFI) DIEP flap. METHODS: A retrospective review was conducted of DIEP flaps for breast reconstruction performed from June 2024 to December 2024 at a single centre in London, United Kingdom. Patients were grouped by incision types: standard (>6 cm) or MFI (≤6 cm). Baseline characteristics, preoperative imaging results, and postoperative outcomes were recorded for comparison. RESULTS: The final cohort included 33 flaps (15 MFI and 18 standard incisions). The median length of stay was significantly lower in the MFI group [4 days (IQR 4-5)] vs. [5 days (IQR 4-6.25)], (p=0.036). The median number of perforators on a single row was significantly lower in the MFI group [1(IQR 1-2)] vs. [2(IQR 2-3)], (p=0.049). Mesh use was significantly higher in the standard incision group (p=0.001). There was no significant difference in operative time (p=0.128). The average MFI rectus sheath incision length was 4.59 cm. No donor-site complications occurred in either group. CONCLUSIONS: A hand-performed MFI DIEP flap reduced hospital stay and mesh use, and was not significantly different in terms of operative time or complication rate to a standard DIEP flap. A scoring system was proposed to optimise patient selection for MFI. The hand-performed technique represents a key step in the surgical learning curve towards laparoscopic and robotic approaches. Further multi-centre prospective studies should be carried out to minimise performance bias and test the proposed framework.