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. 2023 Nov 27;18(11):e0294640.
doi: 10.1371/journal.pone.0294640. eCollection 2023.

Soft tissue prediction in orthognathic surgery: Improving accuracy by means of anatomical details

Federica Ruggiero  1 , Alessandro Borghi  2 , Mirko Bevini  3 , Giovanni Badiali  1   3 , Ottavia Lunari  3 , David Dunaway  4 , Claudio Marchetti  1   3
Affiliations

Soft tissue prediction in orthognathic surgery: Improving accuracy by means of anatomical details

Federica Ruggiero et al. PLoS One. .

Abstract

Three-dimensional virtual simulation of orthognathic surgery is now a well-established method in maxillo-facial surgery. The commercial software packages are still burdened by a consistent imprecision on soft tissue predictions. In this study, the authors produced an anatomically detailed patient specific numerical model for simulation of soft tissue changes in orthognathic surgery. Eight patients were prospectively enrolled. Each patient underwent CBCT and planar x-rays prior to surgery and in addition received an MRI scan. Postoperative soft-tissue change was simulated using Finite Element Modeling (FEM) relying on a patient-specific 3D models generated combining data from preoperative CBCT (hard tissue) scans and MRI scans (muscles and skin). An initial simulation was performed assuming that all the muscles and the other soft tissue had the same material properties (Homogeneous Model). This model was compared with the postoperative CBCT 3D simulation for validation purpose. Design of experiments (DoE) was used to assess the effect of the presence of the muscles considered and of their variation in stiffness. The effect of single muscles was evaluated in specific areas of the midface. The quantitative distance error between the homogeneous model and actual patient surfaces for the midface area was 0.55 mm, standard deviation 2.9 mm. In our experience, including muscles in the numerical simulation of orthognathic surgery, brought an improvement in the quality of the simulation obtained.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
Construction of the model A: axial view on MRI with highlighted segmented muscles in different colors B: sagittal view on CBCT scan whereas bone has been segmented C frontal and D latera view of the merged 3D model obtained with CBCT 3D bone and MRI 3D muscles.
Fig 2
Fig 2
FEM on patient’s model A: model in FE, with constraints applied B: simulation of the bone displacement C: 4 landmarks selected as output in FE for the DoE.
Fig 3
Fig 3
3D model of the patients as imported in Ansys A: frontal view B: lateral view C: graphical visualization of the soft tissue displacement after LeFort 1 simulation.
Fig 4
Fig 4
Comparison by means of colormap (top) and sagittal mid-line cross section (bottom) of postoperative 3D soft tissue reconstruction with H model soft tissue reconstruction.
Fig 5
Fig 5. Box-and-Whisker graphs of the distribution of the difference between the maximum (Nmax, ULmax, Cmax) and minimum (Nmin, ULmin, Cmin) displacement recorded and the respective H model values.
See this image and copyright information in PMC

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