Research on the combination of algorithms and mixed reality for the localization of perforator vessels in anterolateral thigh and free fibula flaps

Purpose This study aims to develop a system that integrates algorithms with mixed reality technology to accurately position perforating vessels during the harvesting of anterolateral thigh and free fibular flaps. The system’s efficacy is compared to that of color Doppler ultrasonography (CDU) to assess its performance in localizing vessels in commonly used lower extremity flaps. Methods Fifty patients requiring anterolateral thigh perforator flaps or free fibular flaps for the reconstruction of maxillofacial tissue defects were randomly divided into two groups: the System Group and the CDU Group, with 25 patients in each group. In the System Group, the flap outline was drawn on the flap donor area of the lower limb, and positioning markers were placed and fixed at the highest points of the outline. After performing lower-limb CTA scanning, the obtained two-dimensional data were reconstructed into a three-dimensional model of all lower-limb tissues and positioning markers using specialized software. This 3D model was then imported into the HoloLens 2. An artificial intelligence algorithm was developed within the HoloLens 2 to automatically align the positioning markers with their 3D models, ultimately achieving registration between the perforator vessels and their 3D models. In the CDU Group, conventional methods were used to locate perforator vessels and mark them on the body surface. For both groups, the perforator flap design was based on the identified vessels. The number of perforator vessels located during surgery and the number actually found were recorded to calculate the accuracy of perforator vessel identification for each technique. The distance between the marked perforator vessel exit points and the actual exit points was measured to determine the margin of error. Additionally, the number of successfully harvested flaps was recorded. Results In the system group, 51 perforating vessel penetration sites were identified in 25 cases, with 53 confirmed during surgery, yielding a 96.2% identification accuracy. In the CDU group, 44 sites were identified, with 49 confirmed during surgery, resulting in an 89.7% accuracy. The distance between the identified and actual penetration sites was 1.68 ± 0.22 mm in the system group, compared to 3.08 ± 0.60 mm in the CDU group. All 25 patients in the system group had successful flap harvests as per the preoperative design. In the CDU group, two patients failed to locate perforating vessels in the designed area, requiring repositioning and subsequent flap harvesting. One patient in the system group developed marginal tissue ischemia and necrosis on postoperative day 7, which healed after debridement. In the CDU group, one patient experienced ischemic necrosis on postoperative day 6, requiring repair with a pectoralis major flap. Conclusion The system developed in this study effectively localizes perforating vessel penetration sites for commonly used lower extremity flaps with high accuracy. This system shows significant potential for application in lower extremity flap harvesting surgeries.