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. 2019 Oct:11768:336-344.
doi: 10.1007/978-3-030-32254-0_38. Epub 2019 Oct 10.

A New Approach of Predicting Facial Changes following Orthognathic Surgery using Realistic Lip Sliding Effect

Affiliations

A New Approach of Predicting Facial Changes following Orthognathic Surgery using Realistic Lip Sliding Effect

Daeseung Kim et al. Med Image Comput Comput Assist Interv. 2019 Oct.

Abstract

Accurate prediction of facial soft-tissue changes following orthognathic surgery is crucial for improving surgical outcome. However, the accuracy of current prediction methods still requires further improvement in clinically critical regions, especially the lips. We develop a novel incremental simulation approach using finite element method (FEM) with realistic lip sliding effect to improve the prediction accuracy in the area around the lips. First, lip-detailed patient-specific FE mesh is generated based on accurately digitized lip surface landmarks. Second, an improved facial soft-tissue change simulation method is developed by applying a lip sliding effect in addition to the mucosa sliding effect. The soft-tissue change is then simulated incrementally to facilitate a natural transition of the facial change and improve the effectiveness of the sliding effects. A preliminary evaluation of prediction accuracy was conducted using retrospective clinical data. The results showed that there was a significant prediction accuracy improvement in the lip region when the realistic lip sliding effect was applied along with the mucosa sliding effect.

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Figures

Fig. 1.
Fig. 1.
Strained lip in (a) mandibular hypoplasia, (b) mandibular hyperplasia.
Fig. 2.
Fig. 2.
Digitization of lip surface points on the parasagittal CT slices. Contours for upper and lower lip surfaces are generated based on the digitized points (red).
Fig. 3.
Fig. 3.
Lip surface mesh generation based on the digitized landmarks (illustrated by upper lip). (a) Frontal view of lip surface extracted from FE mesh. Lip outer surface (blue) and lip inner surface (red). (b) Lip surface and the digitized landmark represented in the grid coordinate system. Digitized lip boundary is shown in black dots. (c) Detailed lip nodes represented in 3D Cartesian coordinate system. (d) Final lip-detailed mesh surface
Fig. 4.
Fig. 4.
An example of lip-detailed mesh. (a) Initial mesh without lip-detailed geometry. (b) Lip-detailed mesh with lip opening.
Fig. 5.
Fig. 5.
The boundary condition (represented on bony surface and FE mesh for illustration purpose. Red: fixed nodes; Green: moving nodes; Pink: sliding nodes; and Green-blue: free nodes.
Fig. 6.
Fig. 6.
Prediction results using three different methods: Traditional method without sliding effect (Method #1); Mucosa sliding effect only (Method #2); Our approach (Method #3) with lip and mucosa sliding effect. Color-coded surface deviation errors between the postoperative face and the prediction results using our approach are in the rightmost column. Blue: preoperative face; Red: postoperative face; Green: prediction results

References

    1. Kim D., et al.: A clinically validated prediction method for facial soft-tissue changes following double-jaw surgery. Medical Physics. 44(8), 4252–4261 (2017) - PMC - PubMed
    1. Kim H., et al.: Anatomically-Driven Soft-Tissue Simulation Strategy for Cranio-Maxillofacial Surgery Using Facial Muscle Template Model. MICCAI 2010. 13(Pt 1), 61–68 (2010) - PubMed
    1. Nadjmi N., et al.: Quantitative validation of a computer-aided maxillofacial planning system, focusing on soft tissue deformations. Annals of maxillofacial surgery. 4(2), 171–175 (2014) - PMC - PubMed
    1. Pan B., et al.: Incremental Kernel Ridge Regression for the Prediction of Soft Tissue Deformations. MICCAI 2012. 15(Pt 1), 99–106 (2012) - PMC - PubMed
    1. Zhang X., et al.: An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation. Biomechanics and Modeling in Mechanobiology. 17(2), 387–402 (2018) - PMC - PubMed

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