Accuracy of three-dimensional soft tissue simulation in bimaxillary osteotomies

Liebregts, Jeroen; Xi, Tong; Timmermans, Maarten; Koning, Martien de; Bergé, Stefaan; Hoppenreijs, T.J.M.; Maal, T.J.J.

doi:10.1016/j.jcms.2014.12.012

Cited by 53 publications

(54 citation statements)

References 32 publications

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“…10 It has also been inferred that the surgical correction in this group of study was less than the study conducted by shafi et al 2013. 8 Various algorithms have been developed and incorporated in commercially available prediction software packages to quantify facial soft tissue changes in three dimensions.…”

Section: Introductionmentioning

confidence: 52%

“…Average mean distances between the real changes and the predicted changes of the soft tissue in response to orthognathic surgery were 0.6mm and the average 90% percentile was below 1.5mm . 10 , the mean absolute prediction error of the entire face was 0.9mm±0.3mm and the mean absolute 90 th percentile was 1.9 mm. The absolute mean prediction error was less than 2mm at all the facial tissue regions except on the lower lip region.…”

Section: Introductionmentioning

confidence: 86%

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The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: An innovative concept

Mundluru

Almukhtar

et al. 2017

International Journal of Oral and Maxillofacial Surgery

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Abstract:The accuracy of three dimensional predictions of soft tissue changes following surgical correction of facial asymmetry has been evaluated in this study. The preoperative (T1) and 6-12 months postoperative (T2) CBCT scans of 13 patients were studied. All patients had surgical correction for facial asymmetry as part of the multidisciplinary treatment protocol.The magnitude of surgical movement was measured; virtual surgery was carried out on the preoperative scans using Maxilim software. The predicted soft tissue changes were compared to the actual postoperative appearance (T2) at specific anatomic facial regions. Mean (signed) distances and the mean (absolute) distances between the predicted and actual 3D surface meshes for each region were calculated. One sample Student t-test was applied. Additionally, a novel directional soft tissue analysis was applied to analyse the accuracy of the prediction of soft tissue. The results showed that the distances between the predicted and actual postoperative soft tissue changes were within 2.0mm (p<0.05) at all regions. The predicted facial morphology was narrower than the actual surgical changes at the cheek regions. Three dimensional soft tissue prediction for the correction of asymmetric cases is clinically acceptable using Maxilim software. Introduction:

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Section: Introductionmentioning

confidence: 52%

Section: Introductionmentioning

confidence: 86%

The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: An innovative concept

Mundluru

Almukhtar

et al. 2017

International Journal of Oral and Maxillofacial Surgery

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“…The magnitude of skeletal movements influences the accuracy of the prediction; moreover, the age of the patient and the use of V-Y closure affect the precision of the predicted model. Low predictability on the upper and lower lip regions is registered once again [22].…”

Section: Work Based On Maxilim Software (3d)mentioning

confidence: 92%

3D Soft-Tissue Prediction Methodologies for Orthognathic Surgery—A Literature Review

et al. 2019

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Three-dimensional technologies have had a wide diffusion in several fields of application throughout the last decades; medicine is no exception and the interest in their introduction in clinical applications has grown with the refinement of such technologies. We focus on the application of 3D methodologies in maxillofacial surgery, where they can give concrete support in surgical planning and in the prediction of involuntary facial soft-tissue changes after planned bony repositioning. The purpose of this literature review is to offer a panorama of the existing prediction methods and software with a comparison of their reliability and to propose a series of still pending issues. Various software are available for surgical planning and for the prediction of tissue displacements, but their reliability is still an unknown variable in respect of the accuracy needed by surgeons. Maxilim, Dolphin and other common planning software provide a realistic result, but with some inaccuracies in specific areas of the face; it also is not totally clear how the prediction is obtained by the software and what is the theoretical model they are based on.

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“…This builds on the work of Liebregts et al, who showed that surfaces acquired from pre- and postoperative CT images can be used to plan mandibular advancement surgery (Liebregts et al, 2015a, b). Their study accurately predicted soft tissue changes postsurgery and was validated in another paper published by this group using the same technique to plan bimaxillary correction (Liebregts et al, 2015a, b). These papers provide important evidence supporting virtual planning of surgery but are limited to nonsyndromic adults and adolescents.…”

Section: Discussionmentioning

confidence: 95%

Combined soft and skeletal tissue modelling of normal and dysmorphic midface postnatal development

Ibrahim

Suttie

Bulstrode

et al. 2016

Journal of Cranio-Maxillofacial Surgery

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Background Midface hypoplasia as exemplified by Treacher Collins Syndrome (TCS) can impair appearance and function. Reconstruction involves multiple invasive surgeries with variable long-term outcomes. This study aims to describe normal and dysmorphic midface postnatal development through combined modelling of skeletal and soft tissues and to develop a surgical evaluation tool. Materials and methods Midface skeletal and soft tissue surfaces were extracted from computed tomography scans of 52 control and 14 TCS children, then analysed using dense surface modelling. The model was used to describe midface growth, morphology, and asymmetry, then evaluate postoperative outcomes. Results Parameters responsible for the greatest variation in midface size and shape showed differences between TCS and controls with close alignment between skeletal and soft tissue models. TCS children exhibited midface dysmorphology and hypoplasia when compared with controls. Asymmetry was also significantly higher in TCS midfaces. Combined modelling was used to evaluate the impact of surgery in one TCS individual who showed normalisation immediately after surgery but reversion towards TCS dysmorphology after 1 year. Conclusion This is the first quantitative analysis of postnatal midface development using combined modelling of skeletal and soft tissues. We also provide an approach for evaluation of surgical outcomes, laying the foundations for future development of a preoperative planning tool.

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Accuracy of three-dimensional soft tissue simulation in bimaxillary osteotomies

Cited by 53 publications

References 32 publications

The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: An innovative concept

The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: An innovative concept

3D Soft-Tissue Prediction Methodologies for Orthognathic Surgery—A Literature Review

Combined soft and skeletal tissue modelling of normal and dysmorphic midface postnatal development

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