From bench to bedside - current clinical and translational challenges in fibula free flap reconstruction.

Fibula free flaps (FFF) represent a working horse for different reconstructive scenarios in facial surgery. While FFF were initially established for mandible reconstruction, advancements in planning for microsurgical techniques have paved the way toward a broader spectrum of indications, including maxillary defects. Essential factors to improve patient outcomes following FFF include minimal donor site morbidity, adequate bone length, and dual blood supply. Yet, persisting clinical and translational challenges hamper the effectiveness of FFF. In the preoperative phase, virtual surgical planning and artificial intelligence tools carry untapped potential, while the intraoperative role of individualized surgical templates and bioprinted prostheses remains to be summarized. Further, the integration of novel flap monitoring technologies into postoperative patient management has been subject to translational and clinical research efforts. Overall, there is a paucity of studies condensing the body of knowledge on emerging technologies and techniques in FFF surgery. Herein, we aim to review current challenges and solution possibilities in FFF. This line of research may serve as a pocket guide on cutting-edge developments and facilitate future targeted research in FFF

From bench to bedside – current clinical and translational challenges in fibula free flap reconstruction

Fibula free flaps (FFF) represent a working horse for different reconstructive scenarios in facial surgery. While FFF were initially established for mandible reconstruction, advancements in planning for microsurgical techniques have paved the way toward a broader spectrum of indications, including maxillary defects. Essential factors to improve patient outcomes following FFF include minimal donor site morbidity, adequate bone length, and dual blood supply. Yet, persisting clinical and translational challenges hamper the effectiveness of FFF. In the preoperative phase, virtual surgical planning and artificial intelligence tools carry untapped potential, while the intraoperative role of individualized surgical templates and bioprinted prostheses remains to be summarized. Further, the integration of novel flap monitoring technologies into postoperative patient management has been subject to translational and clinical research efforts. Overall, there is a paucity of studies condensing the body of knowledge on emerging technologies and techniques in FFF surgery. Herein, we aim to review current challenges and solution possibilities in FFF. This line of research may serve as a pocket guide on cutting-edge developments and facilitate future targeted research in FFF

Creating a statistical shape model to aid in the estimation of incomplete soft tissue segments of the surface of South African faces

Thesis (PhD (Anatomy))--University of Pretoria, 2024.Introduction: A critical gap exists in population-specific data for facial morphology of black South Africans which are essential for the accurate reconstruction of facial features in fields such as aesthetic and reconstructive surgery, prosthodontics and extra-oral facial prosthetics, as well as forensic facial approximations. The objectives of this research were to generate normative reference values of black South African faces for various inter-landmark distances, and to derive a statistical shape model (SSM) of 3D facial shape variation which can be applied to estimate missing soft tissue segments on simulated defective faces. Methods: The study included of 235 computed tomography (CT) and cone-beam computed tomography (CBCT) scans from black South African individuals between the ages of 18 and 87 years. The scans were collected from retrospective records of three medical institutions and excluded individuals that showed conditions potentially affecting facial morphology, including orthodontic treatments, pathological conditions, facial asymmetry, or any history of facial reconstructive surgery. The scans were processed to obtain 3D facial meshes and landmarks were placed at anatomically important loci. For the first objective, inter-landmark distances were calculated, statistically analysed, and compared to published literature on other populations. For the second objective, correspondence of the 3D meshes utilising the landmarks were achieved, and generalised Procrustes analysis and principal component analysis conducted. These steps are crucial in obtaining an SSM comprising the modes of variation and the normal range variance along each mode, which together defines multinormal parameterisation of shape variation. Defect estimations were done by using the SSM to estimate the linear combination of the modes of variation that most closely approximates the intact regions of each face, and estimate the missing regions using a weighted projection onto the modes of variation. Results: Chapter 3 reports on normative facial capulometric measurements specific to the black South African population. It highlights significant differences in facial parameters between sexes and between different populations. The data reveal notable similarities with other African populations, especially in oral features, but significant disparities with non-African groups. Chapter 4 introduces the innovative SSM for extra-oral prosthetic design. This model accurately estimates missing soft tissues, demonstrating a high degree of precision with root mean square errors consistently below 2.58 mm for various facial defects. Conclusion: The normative measurements highlight the unique facial characteristics of the black South African population, demonstrating the necessity of population-specific data in clinical and forensic applications. The development of the SSM represents a novel advancement in digital reconstruction methodologies. It offers a more objective and patient-specific approach in prosthetic design, especially in addressing complex facial defects such as bi-orbital defects or those crossing the facial midline in a demographic that has been largely overlooked in previous research. This model, by reducing the subjectivity and artistic skill previously required in prosthetic design, aligns with the evolving digital trends in medical technology and aims to address specific local needs and challenges in South Africa, and also have potential for global application.UP Doctoral Bursary Bakeng se Afrika Grant/Award Number: 597924-EPP-1-2018-1-ZA-EPPKA2- CBHE-JAnatomyPhD (Anatomy)UnrestrictedFaculty of Health Science