Inferior Medial Genicular Artery Based Tibia Osteocutaneous Flap: Anatomic Study and Clinical Application for Small Composite Digital Defects

Abstract

Reconstruction of composite digital defects presents challenges, as it requires short-pedicled, small flap. In this report, the authors present a new vascularized bone graft based on the inferior medial genicular artery (IMGA) harvested from the proximal medial tibia with overlying skin. The purpose of this study was to investigate the feasibility of this new flap for small composite tissue defects in digits. Methods: This cadaveric dissection study involved 6 fresh frozen cadaver lower extremities and surgical techniques. We recorded the length and diameter of the pedicle. Between October 2023 and February 2024, 9 patients who had small composite tissue defects in digits, metacarpal, and metatarsal bones were treated using this new free flap. The average follow-up period was 9.6 (7-11) months. The Michigan hand outcomes questionnaire (MHQ) scale was used to evaluate postoperative outcomes. Results: Owing to the consistent anatomy of IMGA from cadaveric study, 7 osteocutaneous and 2 bone-only flaps were used to reconstruct the small composite tissue defects. In clinical cases, the average diameter of the artery of the pedicle was 1.2 +/- 0.22 mm. The average pedicle length was 2.5 +/- 0.31 cm. Skin island dimensions ranged from 1 x 2 cm2 to 2 x 4 cm2. Bone flap sizes ranged between 1 x 2 x 1 cm3 and 1 x 4 x 1 cm3. Except for 1 patient, all the flaps survived. In all the patients, bony union was achieved within 2 months postoperatively. The average MHQ score was 75.95 +/- 9.52. No severe donor site morbidity occurred. Scar hypersensitivity in donor site was recorded in 2 patients. Conclusion: This is the first description of IMGA-based tibia osteocutaneous flap and this technique can be another tool for reconstructive surgeons. (c) 2025 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.