Three-Dimensional Soft Tissue Simulation in Orthognathic Surgery

Key points

  • Image and volume fusion precision affects soft tissue simulation accuracy.

  • Soft tissue response is not linear and requires regression algorithms.

  • Soft tissue response algorithms vary with facial type.

  • Simulation accuracy varies with the anatomic region of concern being most accurate in the midline and most variable laterally.

  • Although somewhat flawed, 3-dimensional soft tissue simulation remains the best option for patient communication.

Introduction: nature of the problem

Treatment success in orthognathic surgery is dependent on a stable and functional occlusal correction leading to an outcome that is esthetically pleasing and acceptable to the patient. Although both criteria generally go hand in glove, it is entirely possible to correct the malocclusion and fail to meet the patient’s expectations relative to facial appearance. Legacy planning techniques and careful plan execution have achieved and continue to produce acceptable accuracy when skeletal/occlusal outcome is analyzed. However, the overlying soft tissue response has been difficult to forecast and has been limited to profile representations. Early efforts involved cephalometric tracings from a standardized lateral radiograph. The planned soft tissue profile changes were drawn freehand based on response ratios derived from literature reports of research data. These ratios were often flawed by data averaging and the combination of various facial types to produce a larger sample ( Fig. 1 ). Another option to portray appearance changes involved cutting and reassembly of life-size photographic transparencies to approximate the desired profile changes.

Fig. 1
Soft tissue response taken from legacy research is flawed by data averaging in patients having similar surgery but different lip posture. The lip response to mandibular advancement would be very different in each. This explains the wide peri-oral variation when legacy data are used as the basis for 3D simulation algorithms. ( A-C ) All tracings of patients with mandibular deficiency, but the varying soft tissue posture would require customized soft tissue response ratios for an accurate simulation.

The advent of the personal computer led to efficiency in data gathering and manipulation. Software programs allowed the previously hand-drawn data to be digitized and printed or plotted. Skeletal segments could be moved on-screen, and the soft tissue profile changes were generated using the legacy response data. Program evolution allowed coupling of cephalometric data with a profile digital image that was morphed and provided a simulation that was easier for both clinician and patient to understand. It became obvious, however, that software programs varied in their ability to produce a soft tissue simulation that approximated the actual outcome. Smith and colleagues completed a perceptual study involving orthodontists, surgeons, and lay public scoring the likeness of 2-dimensional (2D) computer-based simulations to the actual treatment outcome. Previous research on accuracy had been landmark specific but failed to look at visual assessment. The following observations resulted from the study:

  • Some programs have default soft tissue response ratios that are “hard coded”

  • Default response ratios were least effective in producing simulations in patients having vertical facial excess or deficiency

  • Programs allowing creation of ratios specific to facial type produce the best simulations

  • Most reported “prediction” ratios are linear

  • Although software response ratios are linear, actual soft tissue response is not

The limitation of 2D computer-aided planning remains the inability to produce other facial views. Patients rarely observe their profile unless from a photo or using multiple mirrors. Although the frontal view can be altered freehand using a combination of computer morphing and cut and paste, changes in the oblique, submentovertex and coronal views cannot be simulated ( Fig. 2 ).

Fig. 2
Freehand treatment simulation is a quick option to demonstrate frontal view changes in asymmetry correction. The image on the right shows soft tissue alteration from correcting the maxillary cant and moving the chin to the midline. Although insufficient for actual planning, the images serve as a basis for further discussion.

Three-dimensional virtual planning in orthognathic surgery

Three-dimensional (3D) reformation of computed tomography (CT) data has been possible since the late 1970s, but its use was limited by image quality and processing time. Development of multidetector row CT in the early 1990s created a viable option. The initial programs for craniofacial virtual planning could import this data but scanner access, radiation concerns and the associated cost limited routine usage. In the late 1990s, the development of flat-panel CT, commonly known as cone beam CT (CBCT), opened the door for widespread use of the technique in multiple disciplines including oral and maxillofacial surgery. Cost largely ceased to be an issue due to much lower hardware expense, machine availability, and low acquisition time. Currently, good resolution with isometric voxels, limited noise, and much lower radiation exposure have made CBCT the imaging choice for 3D planning in the craniofacial region.

Freehand three-dimensional facial morphing

Contemporary 3D virtual planning for orthognathic surgery requires a minimum of a DICOM (Digital Imaging and Communications in Medicine) volume of the area of interest and high-resolution dental models. 3D digital facial images are not necessary but are ideal for patient education. The alternative of freehand 3D facial morphing offers an option for communication during preliminary discussions when the patient has not made a firm commitment to proceeding with treatment. Face Gen was originally developed as a virtual sketch pad for law enforcement and a tool for “high-end” video gamers to create their own avatar ( facegen.com/ ). A frontal and profile digital image are quickly linked by mapping 20 landmarks on the image pair. Algorithms create a wire-mesh model using these landmarks and overlays photorealistic shadowing and pigmentation ( Fig. 3 ). Processing time on a contemporary laptop or workstation is 90 seconds. The resulting image can be rotated to any orientation and morphing can be done by click and drag or using a series of scroll bars that are interactive and modify different facial regions ( Fig. 4 ). The result can be saved in a variety of graphics formats and added to the diagnostic record. The photorealistic image can be seen to compare favorably with the actual treatment outcome ( Figs. 5 and 6 ).

Fig. 3
Three-dimensional freehand morphing is a more sophisticated option for use in preliminary patient discussion. Record acquisition is limited to profile and frontal photographs that are linked by digitizing anatomic soft tissue landmarks ( facegen.com/ ).

Fig. 4
The software quickly creates a wire-mesh face ( A ) that is combined with photorealistic pigmentation and shadowing ( B ) to produce a 3D likeness ( C ) that can be altered. Basic hair styles can be added to create a more realistic image ( D ) ( facegen.com/ ).

Fig. 5
Changes with morphing are based on viewer perception. Options include “click and drag” on the image itself or the use of a series of interconnected sliders that control specific facial regions ( facegen.com/ ).

Aug 5, 2020 | Posted by in Oral and Maxillofacial Surgery | Comments Off on Three-Dimensional Soft Tissue Simulation in Orthognathic Surgery
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