An Open-Source Blender Add-On for Automated Design of Patient-Specific Splint Extensions for Condyle Positioning in Orthognathic Surgery: Workflow and Proof-of-Concept Validation

Background: Patient-specific splints have become an integral component of virtual surgical planning in orthognathic surgery. However, transferring the virtually planned condylar position into the intraoperative setting remains technically challenging and typically requires labor-intensive manual modification of splint geometries. The aim of this study was to develop and describe an open-source Blender add-on that automates the generation of patient-specific splint extensions for condyle positioning and to evaluate its technical feasibility in a proof-of-concept clinical setting. Methods: A Python-based add-on for the open-source 3D modelling software Blender was developed to automate the generation of condyle-positioning splint extensions from stereolithography (STL) models exported by a commercial virtual surgical planning system. The software architecture and processing pipeline comprise facilitated data import, coordinate normalization, extension generation, Boolean processing, optional manual refinement, and STL export for additive manufacturing. The workflow was applied in three patients undergoing bilateral sagittal split osteotomy. Postoperative correspondence between the planned and achieved mandibular positions was assessed using translational and rotational transformation parameters together with qualitative surface distance heatmaps provided by the planning software. Results: The proposed add-on successfully generated patient-specific splint extensions in all three proof-of-concept cases while automating manual modelling steps. All splints were successfully manufactured and applied intraoperatively without redesign. Postoperative evaluation demonstrated good agreement between the virtually planned and achieved mandibular positions, with only small translational and rotational deviations. Descriptive statistical analysis supported the technical feasibility and reproducibility of the proposed workflow. Conclusions: The presented open-source Blender add-on provides a reproducible and extensible workflow for automated generation of patient-specific condyle-positioning splint extensions. The proposed approach successfully integrates virtual surgical planning with additive manufacturing and demonstrates technical feasibility in a proof-of-concept clinical setting. The software establishes a foundation for future validation studies in larger patient cohorts and illustrates the potential of open-source tools to improve transparency, reproducibility, and accessibility in digital orthognathic surgery workflows.