Robotic-assisted harvesting of autologous tissue for microvascular reconstruction: Enhancing precision and minimizing donor site morbidity

Robotic-assisted harvesting of the autologous tissue in microvascular reconstruction has the potential for transformation due to the improved use of precision and reduction of donor site morbidity. Clinical and preclinical studies using robotic-assisted methods to collect tissues, such as deep inferior epigastric perforator and latissimus dorsi flaps, have been observed. A literature review based on PubMed, Medline, Scopus, and Web of Science (2006-2025) was conducted to examine clinical and preclinical studies. The synthesis of data employed a meta-analysis comparing robotic and traditional open procedures, as well as new experimental suggestions that incorporated artificial intelligence-driven vessel maps and a single-port robotic system. Results indicate that robotic systems, such as the Da Vinci and Symani systems, utilise 3D visualisation, tremor filtration, and 7 degrees of wrist articulation to deliver better precision, which is expected to lower donor site complications, including seroma and postoperative pain, by approximately 25% compared to non-robotic methods. Patient-reported outcomes (BREAST-Q, SF-36, etc.) and aesthetic results have improved significantly, particularly in breast reconstruction and the head and neck. New-generation single-port robotics also result in fewer scars, and AI implementation can reduce anastomosis time by 1520%. Although they require more operative time due to technical complexity, robotic methods hold promise for transformation in reconstructive surgery. Multicenter trials, cost-efficient innovations, and the incorporation of machine learning are the priorities in future research to increase clinical integration and confirm the effectiveness of such changes.