Digital Orthodontic Setups in Orthognathic Surgery: Evaluating Predictability and Precision of the Workflow in...

Background: Inadequate presurgical planning is a key contributor to suboptimal outcomes in orthognathic surgery. This study aims to assess the accuracy of a digital surgical planning workflow conducted prior to any orthodontic intervention. Methods: Digital planning was performed for 26 patients before orthodontic treatment (T0) and compared to the actual preoperative planning (T1). Digitized plaster casts were merged with CBCT data and converted to orthodontic setups to create a 3D virtual head model. After voxel-based registration of T0 and T1, dental arches were virtually osteotomized and repositioned according to planned outcomes. These T0 segments were then aligned with T1 planning using bony landmarks of the maxilla. Anatomical landmarks were used to construct virtual triangles on maxillary and mandibular segments, enabling assessment of positional and orientational differences. Transformations between T0 and T1 were translated into clinically meaningful metrics. Results: Significant differences were found between T0 and T1 at the dental level. T1 exhibited a greater clockwise rotation of the dental maxilla (mean: 2.85°) and a leftward translation of the mandibular dental arch (mean: 1.19 mm). In SARME cases, the bony mandible showed larger anti-clockwise roll differences. Pitch variations were also more pronounced in maxillary extraction cases, with both the dental maxilla and bony mandible demonstrating increased clockwise rotations. Conclusions: The proposed orthognathic surgical planning workflow shows potential for simulating mandibular outcomes but lacks dental-level accuracy, especially in maxillary anterior torque. While mandibular bony outcome predictions align reasonably with pretreatment planning, notable discrepancies exceed clinically acceptable thresholds. Current accuracy limits routine use; further refinement and validation in larger, homogeneous patient groups are needed to enhance clinical reliability and applicability.