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Updated: Jun 30, 2026

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
Published on: January 28, 2020
AI-Assisted Soft Tissue Virtual Planning in Computer-Assisted Jaw Reconstruction with Fibula Free Flaps
Jane J Pu1, Dinggang Shen2,3, Xiao Fan4
1Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Summary:
Computer-assisted surgery (CAS) has transformed jaw reconstruction, enabling one-stage functional reconstruction with fibula bone segmentation and dental implantation. However, virtual surgical planning (VSP) without consideration of perforator position and soft tissue can lead to a difficult flap inset. Despite the rapid development of bony planning in recent years, little progress has been made in planning soft tissue, which limits the predictable execution of the plan.An artificial intelligence-enabled automatic program for segmenting skin perforating vessels was developed. The models of skin perforating vessels were incorporated into the VSP workflow when designing osteotomy and dental implantation sites. During the surgery, the vessel models were automatically registered and projected onto the patient's skin for goggle-free augmented-reality (AR) flap design and harvest. Consecutive patients undergoing FFF reconstructions participated in this pilot study. The perforators identified by the AI program and during surgery were compared.Seventy-nine skin perforators in 26 consecutive patients were mapped out using the AI program and incorporated into the routine VSP workflow. No intraoperative adjustments to the plan were required due to the perforator location. The overall predictive accuracy of the skin perforator segmentation was 92.8%.For the first time, our study employed a combined AI and AR approach for preoperative planning and intraoperative execution of the soft tissue component in computer-assisted jaw reconstruction, demonstrating promising outcomes. This study demonstrated the potential of AI and AR to improve the predictability of functional jaw reconstruction.
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