Facial Conformation Meshes for Orthognathic Surgery

Plain-language summary

This study is a retrospective analysis that evaluates the accuracy of 3D soft tissue simulation in bimaxillary orthognathic surgery for Class III dentofacial deformities. The study integrates segmented 3D facial conformation meshes and regional aesthetic subunits to enhance soft tissue prediction accuracy. Key Aspects of the Study: Study Design: Retrospective analysis based on existing CBCT scans of patients who have undergone maxillary advancement and mandibular setback surgery. Objective: To assess the accuracy of soft tissue predictions using Dolphin software in different facial regions, particularly in midline vs. lateral regions. Methodology: .CBCT superimposition using voxel-based registration. .Soft tissue surface analysis via generic mesh conformation and dense correspondence analysis. .Error assessment in X, Y, Z dimensions rather than Euclidean distance. .Color-coded maps for visualizing prediction accuracy. Clinical Relevance: The study aims to refine 3D prediction models for orthognathic surgery planning, making them more precise and reliable. Key innovation: Modifying the aesthetic unit segmentation approach for a clinically and statistically relevant assessment of soft tissue changes. Findings will contribute to improving surgical outcome predictability and optimizing treatment planning in maxillofacial surgery. Ethical Considerations: No patient recruitment; the study relies solely on existing anonymized CBCT scans. Ethical approval and waiver of informed consent will be sought from the Institutional Review Board (IRB). This research aligns with modern advancements in 3D facial prediction technology, aiming to enhance precision and clinical applicability in orthognathic surgery.

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