A prototype computer-assisted system for automatic three-dimensional orthognathic surgery planning: an initial retrospective study.

Authors

F Bouffleur, C A J Bauer, R Kühle, N Hagen, S Richter, J Hoffmann, C Freudlsperger, H Dickhaus, U Eisenmann

Published in

International journal of oral and maxillofacial surgery. Sep 08, 2026. Epub Sep 08, 2026.

Abstract

Preoperative planning is crucial in orthognathic surgery, addressing both functional and aesthetic aspects in young adults. The current state-of-the-art still relies on fully manual virtual surgery planning despite the availability of detailed three-dimensional imaging. A prototype system for orthognathic surgery planning was developed that transforms manually identified landmarks into automated planning proposals by embedding established cephalometric rules, photoanalysis and clinical expert knowledge into an algorithmic framework. To evaluate the prototype, an initial retrospective study including 20 patients who underwent bimaxillary orthognathic surgery was performed. The study population was balanced for gender and skeletal class. For each case automatic planning proposals were compared with state-of-the-art virtual surgery planning. Quantitative differences between both planning approaches were analysed across all six degrees of freedom. In addition, a subgroup analysis according to skeletal class (class II vs class III) was conducted to assess potential class-specific deviations. Statistical comparisons were performed using t-tests or Mann-Whitney U-tests depending on data distribution (P < 0.05). Agreement between prototype and expert planning was assessed using Bland-Altman analysis and intra-class correlation coefficients. Results showed good agreement in most degrees of freedom. Statistically significant differences in planning results were noted in the Pitch dimension (Expert: 0.88° ± 4.46; Planning system: 5.72° ± 5.7; P = 0.0049; CI: 1.56, 8.12). The prototype generally produced clinically reasonable planning propositions within the scope of the preliminary evaluation study. Incorporating additional cephalometric analyses and optimising the algorithm will likely enhance the systems performance.

PMID:
42711161
Bibliographic data and abstract were imported from PubMed on 09 Sep 2026.

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