Publications by authors named "Jaime Gateno"

67 Publications

A novel incremental simulation of facial changes following orthognathic surgery using FEM with realistic lip sliding effect.

Med Image Anal 2021 May 5;72:102095. Epub 2021 May 5.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, 6560 Fannin St, Houston, TX 77030, USA; Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, 407 E 61st St, New York, NY 10065, USA. Electronic address:

Accurate prediction of facial soft-tissue changes following orthognathic surgery is crucial for surgical outcome improvement. We developed a novel incremental simulation approach using finite element method (FEM) with a realistic lip sliding effect to improve the prediction accuracy in the lip region. First, a lip-detailed mesh is generated based on accurately digitized lip surface points. Second, an improved facial soft-tissue change simulation method is developed by applying a lip sliding effect along with the mucosa sliding effect. Finally, the orthognathic surgery initiated soft-tissue change is simulated incrementally to facilitate a natural transition of the facial change and improve the effectiveness of the sliding effects. Our method was quantitatively validated using 35 retrospective clinical data sets by comparing it to the traditional FEM simulation method and the FEM simulation method with mucosa sliding effect only. The surface deviation error of our method showed significant improvement in the upper and lower lips over the other two prior methods. In addition, the evaluation results using our lip-shape analysis, which reflects clinician's qualitative evaluation, also proved significant improvement of the lip prediction accuracy of our method for the lower lip and both upper and lower lips as a whole compared to the other two methods. In conclusion, the prediction accuracy in the clinically critical region, i.e., the lips, significantly improved after applying incremental simulation with realistic lip sliding effect compared with the FEM simulation methods without the lip sliding effect.
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http://dx.doi.org/10.1016/j.media.2021.102095DOI Listing
May 2021

Diverse data augmentation for learning image segmentation with cross-modality annotations.

Med Image Anal 2021 Jul 20;71:102060. Epub 2021 Apr 20.

Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina, Chapel Hill, NC, USA. Electronic address:

The dearth of annotated data is a major hurdle in building reliable image segmentation models. Manual annotation of medical images is tedious, time-consuming, and significantly variable across imaging modalities. The need for annotation can be ameliorated by leveraging an annotation-rich source modality in learning a segmentation model for an annotation-poor target modality. In this paper, we introduce a diverse data augmentation generative adversarial network (DDA-GAN) to train a segmentation model for an unannotated target image domain by borrowing information from an annotated source image domain. This is achieved by generating diverse augmented data for the target domain by one-to-many source-to-target translation. The DDA-GAN uses unpaired images from the source and target domains and is an end-to-end convolutional neural network that (i) explicitly disentangles domain-invariant structural features related to segmentation from domain-specific appearance features, (ii) combines structural features from the source domain with appearance features randomly sampled from the target domain for data augmentation, and (iii) train the segmentation model with the augmented data in the target domain and the annotations from the source domain. The effectiveness of our method is demonstrated both qualitatively and quantitatively in comparison with the state of the art for segmentation of craniomaxillofacial bony structures via MRI and cardiac substructures via CT.
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http://dx.doi.org/10.1016/j.media.2021.102060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184609PMC
July 2021

Estimating Reference Bony Shape Models for Orthognathic Surgical Planning Using 3D Point-Cloud Deep Learning.

IEEE J Biomed Health Inform 2021 Jan 26;PP. Epub 2021 Jan 26.

Orthognathic surgical outcomes rely heavily on the quality of surgical planning. Automatic estimation of a reference facial bone shape significantly reduces experience-dependent variability and improves planning accuracy and efficiency. We propose an end-to-end deep learning framework to estimate patient-specific reference bony shape models for patients with orthognathic deformities. Specifically, we apply a point-cloud network to learn a vertex-wise deformation field from a patients deformed bony shape, represented as a point cloud. The estimated deformation field is then used to correct the deformed bony shape to output a patient-specific reference bony surface model. To train our network effectively, we introduce a simulation strategy to synthesize deformed bones from any given normal bone, producing a relatively large and diverse dataset of shapes for training. Our method was evaluated using both synthetic and real patient data. Experimental results show that our framework estimates realistic reference bony shape models for patients with varying deformities. The performance of our method is consistently better than an existing method and several deep point-cloud networks. Our end-to-end estimation framework based on geometric deep learning shows great potential for improving clinical workflows.
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http://dx.doi.org/10.1109/JBHI.2021.3054494DOI Listing
January 2021

A Better Understanding of Unilateral Condylar Hyperplasia of the Mandible.

J Oral Maxillofac Surg 2021 May 29;79(5):1122-1132. Epub 2020 Dec 29.

Director of the Surgical Planning Laboratory, Oral and Maxillofacial Surgery Department, Houston Methodist Research Institute; Professor of Oral and Maxillofacial Surgery, Houston Methodist Academic Institute, Houston, TX; and Professor of Surgery (Oral and Maxillofacial Surgery), Weill-Cornell Medical College, New York, NY. Electronic address:

Purpose: Our current understanding of unilateral condylar hyperplasia (UCH) was put forth by Obwegeser. He hypothesized that UCH is 2 separate conditions: hemimandibular hyperplasia and hemimandibular elongation. This hypothesis was based on the following 3 assumptions: 1) the direction of overgrowth, in UCH, is bimodal-vertical or horizontal, with rare cases growing obliquely; 2) UCH can expand a hemimandible with and without significant condylar enlargement; and 3) there is an association between the condylar expansion and the direction of overgrowth-minimal expansion resulting in horizontal growth and significant enlargement causing vertical displacement. The purpose of this study was to test these assumptions.

Patients And Methods: We analyzed the computed tomography scans of 40 patients with UCH. First, we used a Silverman Cluster analysis to determine how the direction of overgrowth is distributed in the UCH population. Next, we evaluated the relationship between hemimandibular overgrowth and condylar enlargement to confirm that overgrowth can occur independently of condylar expansion. Finally, we assessed the relationship between the degree of condylar enlargement and the direction of overgrowth to ascertain if condylar expansion determines the direction of growth.

Results: Our first investigation demonstrates that the general impression that UCH is bimodal is wrong. The growth vectors in UCH are unimodally distributed, with the vast majority of cases growing diagonally. Our second investigation confirms the observation that UCH can expand a hemimandible with and without significant condylar enlargement. Our last investigation determined that in UCH, there is no association between the degree of condylar expansion and the direction of the overgrowth.

Conclusions: The results of this study disprove the idea that UCH is 2 different conditions: hemimandibular hyperplasia and hemimandibular elongation. It also provides new insights about the pathophysiology of UCH.
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http://dx.doi.org/10.1016/j.joms.2020.12.034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096674PMC
May 2021

Validity of Medical Insurance Guidelines for Orthognathic Surgery.

J Oral Maxillofac Surg 2021 Mar 24;79(3):672-684. Epub 2020 Nov 24.

Director of Surgical Planning Laboratory, Oral and Maxillofacial Surgery Department, Houston Methodist Hospital, Houston, TX; Professor of Oral and Maxillofacial Surgery, Houston Methodist Academic Institute, Houston, TX; and Professor of Surgery (Oral and Maxillofacial Surgery), Weill-Cornell Medical College, New York, NY. Electronic address:

Purpose: The purpose of this study was to assess the validity of the medical insurance guidelines for orthognathic surgery used by the major American medical insurance companies.

Materials And Methods: This study assessed the validity of the medical insurance guidelines for orthognathic surgery used by Aetna, Anthem Blue Cross Blue Shield (BCBS), Cigna, Humana, and UnitedHealthcare (UHC). To evaluate the validity, we calculated the approval and denial rates of the 5 guidelines when we used them to assess the medical necessity for a control group of carefully selected patients. Patients were included in the control group if they met the criteria of a "prudent provider," crafted for this study. All rejected cases were analyzed to determine the root cause of the denials. The validity of the guidelines was also ascertained by determining their completeness and correctness.

Results: The current study proves that no insurance guideline is in agreement with the criteria of a "prudent provider." When applied to carefully chosen patients, the requirements of BCBS, Aetna, Humana, and Cigna produce modest rejection rates of 6 to 12%. UHC is an outlier. Its guideline rejects 86% of patients, a rate about 7 times higher than its peers. Insurance guidelines disqualified patients for 3 different reasons: 1) no significant jaw deformity, 2) no demonstrable health impairment, and 3) the etiology of the condition is not a covered benefit. Additional evaluations demonstrate that the private insurance guidelines are incomplete, and at times, incorrect.

Conclusions: This study shows that the medical insurance guidelines for orthognathic surgery used by the major American medical insurance plans need revision. The most consequential flaw was considering etiology in judging medical necessity. Fortunately, only one company adopted this policy. Moreover, all guidelines have omissions and errors in the way jaw deformity is determined and how health impairment is determined.
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http://dx.doi.org/10.1016/j.joms.2020.11.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925386PMC
March 2021

Anatomy-Regularized Representation Learning for Cross-Modality Medical Image Segmentation.

IEEE Trans Med Imaging 2021 01 29;40(1):274-285. Epub 2020 Dec 29.

An increasing number of studies are leveraging unsupervised cross-modality synthesis to mitigate the limited label problem in training medical image segmentation models. They typically transfer ground truth annotations from a label-rich imaging modality to a label-lacking imaging modality, under an assumption that different modalities share the same anatomical structure information. However, since these methods commonly use voxel/pixel-wise cycle-consistency to regularize the mappings between modalities, high-level semantic information is not necessarily preserved. In this paper, we propose a novel anatomy-regularized representation learning approach for segmentation-oriented cross-modality image synthesis. It learns a common feature encoding across different modalities to form a shared latent space, where 1) the input and its synthesis present consistent anatomical structure information, and 2) the transformation between two images in one domain is preserved by their syntheses in another domain. We applied our method to the tasks of cross-modality skull segmentation and cardiac substructure segmentation. Experimental results demonstrate the superiority of our method in comparison with state-of-the-art cross-modality medical image segmentation methods.
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http://dx.doi.org/10.1109/TMI.2020.3025133DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120796PMC
January 2021

Estimating Reference Shape Model for Personalized Surgical Reconstruction of Craniomaxillofacial Defects.

IEEE Trans Biomed Eng 2021 Feb 20;68(2):362-373. Epub 2021 Jan 20.

Objective: To estimate a patient-specific reference bone shape model for a patient with craniomaxillofacial (CMF) defects due to facial trauma.

Methods: We proposed an automatic facial bone shape estimation framework using pre-traumatic conventional portrait photos and post-traumatic head computed tomography (CT) scans via a 3D face reconstruction and a deformable shape model. Specifically, a three-dimensional (3D) face was first reconstructed from the patient's pre-traumatic portrait photos. Second, a correlation model between the skin and bone surfaces was constructed using a sparse representation based on the CT images of training normal subjects. Third, by feeding the reconstructed 3D face into the correlation model, an initial reference shape model was generated. In addition, we refined the initial estimation by applying non-rigid surface matching between the initially estimated shape and the patient's post-traumatic bone based on the adaptive-focus deformable shape model (AFDSM). Furthermore, a statistical shape model, built from the training normal subjects, was utilized to constrain the deformation process to avoid overfitting.

Results And Conclusion: The proposed method was evaluated using both synthetic and real patient data. Experimental results show that the patient's abnormal facial bony structure can be recovered using our method, and the estimated reference shape model is considered clinically acceptable by an experienced CMF surgeon.

Significance: The proposed method is more suitable to the complex CMF defects for CMF reconstructive surgical planning.
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http://dx.doi.org/10.1109/TBME.2020.2990586DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163108PMC
February 2021

An automatic approach to establish clinically desired final dental occlusion for one-piece maxillary orthognathic surgery.

Int J Comput Assist Radiol Surg 2020 Nov 25;15(11):1763-1773. Epub 2020 Feb 25.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, TX, USA.

Purpose: One critical step in routine orthognathic surgery is to reestablish a desired final dental occlusion. Traditionally, the final occlusion is established by hand articulating stone dental models. To date, there are still no effective solutions to establish the final occlusion in computer-aided surgical simulation. In this study, we consider the most common one-piece maxillary orthognathic surgery and propose a three-stage approach to digitally and automatically establish the desired final dental occlusion.

Methods: The process includes three stages: (1) extraction of points of interest and teeth landmarks from a pair of upper and lower dental models; (2) establishment of Midline-Canine-Molar (M-C-M) relationship following the clinical criteria on these three regions; and (3) fine alignment of upper and lower teeth with maximum contacts without breaking the established M-C-M relationship. Our method has been quantitatively and qualitatively validated using 18 pairs of dental models.

Results: Qualitatively, experienced orthodontists assess the algorithm-articulated and hand-articulated occlusions while being blind to the methods used. They agreed that occlusion results of the two methods are equally good. Quantitatively, we measure and compare the distances between selected landmarks on upper and lower teeth for both algorithm-articulated and hand-articulated occlusions. The results showed that there was no statistically significant difference between the algorithm-articulated and hand-articulated occlusions.

Conclusion: The proposed three-stage automatic dental articulation method is able to articulate the digital dental model to the clinically desired final occlusion accurately and efficiently. It allows doctors to completely eliminate the use of stone dental models in the future.
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http://dx.doi.org/10.1007/s11548-020-02125-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484002PMC
November 2020

Clinical Evaluation of Digital Dental Articulation for One-Piece Maxillary Surgery.

J Oral Maxillofac Surg 2020 May 7;78(5):799-805. Epub 2020 Jan 7.

Professor, Department of Oral and Maxillofacial Surgery, and Director, Surgical Planning Laboratory, Houston Methodist, Houston, TX; and Professor of Surgery (Oral and Maxillofacial Surgery) Department of Surgery, Joan & Sanford I. Weill Medical College of Cornell University, New York, NY. Electronic address:

Purpose: Methods for digital dental alignment are not readily available to automatically articulate the upper and lower jaw models. The purpose of the present study was to assess the accuracy of our newly developed 3-stage automatic digital articulation approach by comparing it with the reference standard of orthodontist-articulated occlusion.

Materials And Methods: Thirty pairs of stone dental models from double-jaw orthognathic surgery patients who had undergone 1-piece Le Fort I osteotomy were used. Two experienced orthodontists manually articulated the models to their perceived final occlusion for surgery. Each pair of models was then scanned twice-while in the orthodontist-determined occlusion and again with the upper and lower models separated and positioned randomly. The separately scanned models were automatically articulated to the final occlusion using our 3-stage algorithm, resulting in an algorithm-articulated occlusion (experimental group). The models scanned together represented the manually articulated occlusion (control group). A qualitative evaluation was completed using a 3-point categorical scale by the same orthodontists, who were unaware of the methods used to articulate the models. A quantitative evaluation was also completed to determine whether any differences were present in the midline, canine, and molar relationships between the algorithm-determined and manually articulated occlusions using repeated measures analysis of variance (ANOVA). Finally, the mean ± standard deviation values were computed to determine the differences between the 2 methods.

Results: The results of the qualitative evaluation revealed that all the algorithm-articulated occlusions were as good as the manually articulated ones. The results of the repeated measures ANOVA found no statistically significant differences between the 2 methods [F(1,28) = 0.03; P = .87]. The mean differences between the 2 methods were all within 0.2 mm.

Conclusions: The results of our study have demonstrated that dental models can be accurately, reliably, and automatically articulated using our 3-stage algorithm approach, meeting the reference standard of orthodontist-articulated occlusion.
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http://dx.doi.org/10.1016/j.joms.2019.12.021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265171PMC
May 2020

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

Med Image Comput Comput Assist Interv 2019 Oct 10;11768:336-344. Epub 2019 Oct 10.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, TX, USA.

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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http://dx.doi.org/10.1007/978-3-030-32254-0_38DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934101PMC
October 2019

An Automatic Approach to Reestablish Final Dental Occlusion for 1-Piece Maxillary Orthognathic Surgery.

Med Image Comput Comput Assist Interv 2019 Oct 10;11768:345-353. Epub 2019 Oct 10.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, TX.

Accurately establishing a desired final dental occlusion of the upper and lower teeth is a critical step in orthognathic surgical planning. Traditionally, the final occlusion is established by hand-articulating the stone dental models. However, this process is inappropriate to digitally plan the orthognathic surgery using computer-aided surgical simulation. To date, there is no effective method of digitally establishing final occlusion. We propose a 3-stage approach to digitally and automatically establish a desired final dental occlusion for 1-piece maxillary orthognathic surgery, including: 1) to automatically extract points of interest and four key teeth landmarks from the occlusal surfaces; 2) to align the upper and lower teeth to a clinically desired Midline-Canine-Molar relationship by minimization of sum of distances between them; and 3) to finely align the upper and lower teeth to a maximum contact with the constraints of collision and clinical criteria. The proposed method was evaluated qualitatively and quantitatively and proved to be effective and accurate.
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http://dx.doi.org/10.1007/978-3-030-32254-0_39DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914315PMC
October 2019

Estimating Reference Bony Shape Model for Personalized Surgical Reconstruction of Posttraumatic Facial Defects.

Med Image Comput Comput Assist Interv 2019 Oct 10;11768:327-335. Epub 2019 Oct 10.

BRIC and Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, USA.

In this paper, we introduce a method for estimating patient-specific reference bony shape models for planning of reconstructive surgery for patients with acquired craniomaxillofacial (CMF) trauma. We propose an automatic bony shape estimation framework using pre-traumatic portrait photographs and post-traumatic head computed tomography (CT) scans. A 3D facial surface is first reconstructed from the patient's pre-traumatic photographs. An initial estimation of the patient's normal bony shape is then obtained with the reconstructed facial surface via sparse representation using a dictionary of paired facial and bony surfaces of normal subjects. We further refine the bony shape model by deforming the initial bony shape model to the post-traumatic 3D CT bony model, regularized by a statistical shape model built from a database of normal subjects. Experimental results show that our method is capable of effectively recovering the patient's normal facial bony shape in regions with defects, allowing CMF surgical planning to be performed precisely for a wider range of defects caused by trauma.
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http://dx.doi.org/10.1007/978-3-030-32254-0_37DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6910247PMC
October 2019

One-Shot Generative Adversarial Learning for MRI Segmentation of Craniomaxillofacial Bony Structures.

IEEE Trans Med Imaging 2020 03 14;39(3):787-796. Epub 2019 Aug 14.

Compared to computed tomography (CT), magnetic resonance imaging (MRI) delineation of craniomaxillofacial (CMF) bony structures can avoid harmful radiation exposure. However, bony boundaries are blurry in MRI, and structural information needs to be borrowed from CT during the training. This is challenging since paired MRI-CT data are typically scarce. In this paper, we propose to make full use of unpaired data, which are typically abundant, along with a single paired MRI-CT data to construct a one-shot generative adversarial model for automated MRI segmentation of CMF bony structures. Our model consists of a cross-modality image synthesis sub-network, which learns the mapping between CT and MRI, and an MRI segmentation sub-network. These two sub-networks are trained jointly in an end-to-end manner. Moreover, in the training phase, a neighbor-based anchoring method is proposed to reduce the ambiguity problem inherent in cross-modality synthesis, and a feature-matching-based semantic consistency constraint is proposed to encourage segmentation-oriented MRI synthesis. Experimental results demonstrate the superiority of our method both qualitatively and quantitatively in comparison with the state-of-the-art MRI segmentation methods.
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http://dx.doi.org/10.1109/TMI.2019.2935409DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219540PMC
March 2020

Both the Observer's Expertise and the Subject's Facial Symmetry Can Affect Anatomical Position of the Head.

J Oral Maxillofac Surg 2019 Feb 11;77(2):406.e1-406.e9. Epub 2018 Oct 11.

Director, Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, TX; Professor of Oral and Maxillofacial Surgery, Institute for Academic Medicine, Houston Methodist Hospital, Houston, TX; and Professor of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, NY. Electronic address:

Purpose: It is easier to judge facial deformity when the patient's head is in anatomic position. The purposes of this study were to determine 1) whether a group of expert observers would agree more than a group of nonexperts on what is the correct anatomic position of the head, 2) whether there would be more variation in the alignment of an asymmetrical face compared with a symmetrical one, and 3) whether the alignments of experts would be more repeatable than those of nonexperts.

Materials And Methods: Thirty-one orthodontists (experts) and 31 dental students (nonexperts) were recruited for this mixed-model study. They were shown randomly oriented 3-dimensional head photographs of an adult with a symmetrical face and an adolescent with an asymmetrical face. In viewing software, the observers oriented the images into anatomic position. They repeated the orientations 4 weeks later. Data were analyzed using a generalized linear model and Bland-Altman plots. The primary predictor variables were experience and symmetry status. The outcome variable was the anatomic position of the head. The other variables of interest included time and orientation direction.

Results: There was a statistically significant difference between measurements completed by experts and nonexperts (F = 14.83; P < .01). The interaction between expertise and symmetrical status showed a statistically significant difference between symmetrical and asymmetrical faces in the expert and nonexpert groups (F = 9.93; P = .003). The interaction between expertise and time showed a statistically significant difference in measurement over time in the expert and nonexpert groups (F = 4.66; P = .03).

Conclusions: The study shows that experts can set a head into anatomic position better than nonexperts. In addition, facial asymmetry has a profound effect on the ability of an observer to align a head in the correct anatomic position. Moreover, observer-guided alignment is not reproducible.
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http://dx.doi.org/10.1016/j.joms.2018.09.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359970PMC
February 2019

An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation.

Biomech Model Mechanobiol 2018 Apr 12;17(2):387-402. Epub 2017 Oct 12.

Department of Oral and Craniomaxillofacial Surgery, Shanghai 9th Peoples Hospital, Shanghai Jiaotong University School of Medicine and Shanghai Key Laboratory of Stomatology, Shanghai, China.

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians' need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change.
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http://dx.doi.org/10.1007/s10237-017-0967-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5845478PMC
April 2018

A clinically validated prediction method for facial soft-tissue changes following double-jaw surgery.

Med Phys 2017 Aug 10;44(8):4252-4261. Epub 2017 Jul 10.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, TX, 77030, USA.

Purpose: It is clinically important to accurately predict facial soft-tissue changes prior to orthognathic surgery. However, the current simulation methods are problematic, especially in anatomic regions of clinical significance, e.g., the nose, lips, and chin. We developed a new 3-stage finite element method (FEM) approach that incorporates realistic tissue sliding to improve such prediction.

Methods: In Stage One, soft-tissue change was simulated, using FEM with patient-specific mesh models generated from our previously developed eFace template. Postoperative bone movement was applied on the patient mesh model with standard FEM boundary conditions. In Stage Two, the simulation was improved by implementing sliding effects between gum tissue and teeth using a nodal force constraint scheme. In Stage Three, the result of the tissue sliding effect was further enhanced by reassigning the soft-tissue-bone mapping and boundary conditions using nodal spatial constraint. Finally, our methods have been quantitatively and qualitatively validated using 40 retrospectively evaluated patient cases by comparing it to the traditional FEM method and the FEM with sliding effect, using a nodal force constraint method.

Results: The results showed that our method was better than the other two methods. Using our method, the quantitative distance errors between predicted and actual patient surfaces for the entire face and any subregions thereof were below 1.5 mm. The overall soft-tissue change prediction was accurate to within 1.1 ± 0.3 mm, with the accuracy around the upper and lower lip regions of 1.2 ± 0.7 mm and 1.5 ± 0.7 mm, respectively. The results of qualitative evaluation completed by clinical experts showed an improvement of 46% in acceptance rate compared to the traditional FEM simulation. More than 80% of the result of our approach was considered acceptable in comparison with 55% and 50% following the other two methods.

Conclusion: The FEM simulation method with improved sliding effect showed significant accuracy improvement in the whole face and the clinically significant regions (i.e., nose and lips) in comparison with the other published FEM methods, with or without sliding effect using a nodal force constraint. The qualitative validation also proved the clinical feasibility of the developed approach.
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http://dx.doi.org/10.1002/mp.12391DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553697PMC
August 2017

Design, development and clinical validation of computer-aided surgical simulation system for streamlined orthognathic surgical planning.

Int J Comput Assist Radiol Surg 2017 Dec 21;12(12):2129-2143. Epub 2017 Apr 21.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, Houston, TX, 77030, USA.

Purpose: There are many proven problems associated with traditional surgical planning methods for orthognathic surgery. To address these problems, we developed a computer-aided surgical simulation (CASS) system, the AnatomicAligner, to plan orthognathic surgery following our streamlined clinical protocol.

Methods: The system includes six modules: image segmentation and three-dimensional (3D) reconstruction, registration and reorientation of models to neutral head posture, 3D cephalometric analysis, virtual osteotomy, surgical simulation, and surgical splint generation. The accuracy of the system was validated in a stepwise fashion: first to evaluate the accuracy of AnatomicAligner using 30 sets of patient data, then to evaluate the fitting of splints generated by AnatomicAligner using 10 sets of patient data. The industrial gold standard system, Mimics, was used as the reference.

Result: When comparing the results of segmentation, virtual osteotomy and transformation achieved with AnatomicAligner to the ones achieved with Mimics, the absolute deviation between the two systems was clinically insignificant. The average surface deviation between the two models after 3D model reconstruction in AnatomicAligner and Mimics was 0.3 mm with a standard deviation (SD) of 0.03 mm. All the average surface deviations between the two models after virtual osteotomy and transformations were smaller than 0.01 mm with a SD of 0.01 mm. In addition, the fitting of splints generated by AnatomicAligner was at least as good as the ones generated by Mimics.

Conclusion: We successfully developed a CASS system, the AnatomicAligner, for planning orthognathic surgery following the streamlined planning protocol. The system has been proven accurate. AnatomicAligner will soon be available freely to the boarder clinical and research communities.
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http://dx.doi.org/10.1007/s11548-017-1585-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664166PMC
December 2017

A Geometric Classification of Jaw Deformities.

J Oral Maxillofac Surg 2015 Dec;73(12 Suppl):S26-31

Professor and Chief, Division of Pediatric Plastic Surgery, Department of Pediatric Surgery, The University of Texas Health Science Center at Houston, Houston, TX.

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http://dx.doi.org/10.1016/j.joms.2015.05.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4666701PMC
December 2015

An eFace-Template Method for Efficiently Generating Patient-Specific Anatomically-Detailed Facial Soft Tissue FE Models for Craniomaxillofacial Surgery Simulation.

Ann Biomed Eng 2016 May 13;44(5):1656-71. Epub 2015 Oct 13.

Department of Oral and Maxillofacial Surgery, Houston Methodist Research Institute, 6560 Fannin Street, Suite 1280, Houston, TX, 77030, USA.

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft-tissue changes following osteotomy. This can only be accomplished on an anatomically-detailed facial soft tissue model. However, current anatomically-detailed facial soft tissue model generation is not appropriate for clinical applications due to the time intensive nature of manual segmentation and volumetric mesh generation. This paper presents a novel semi-automatic approach, named eFace-template method, for efficiently and accurately generating a patient-specific facial soft tissue model. Our novel approach is based on the volumetric deformation of an anatomically-detailed template to be fitted to the shape of each individual patient. The adaptation of the template is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. This methodology was validated using 4 visible human datasets (regarded as gold standards) and 30 patient models. The results indicated that our approach can accurately preserve the internal anatomical correspondence (i.e., muscles) for finite element modeling. Additionally, our hybrid approach was able to achieve an optimal balance among the patient shape fitting accuracy, anatomical correspondence and mesh quality. Furthermore, the statistical analysis showed that our hybrid approach was superior to two previously published methods: mesh-matching and landmark-based transformation. Ultimately, our eFace-template method can be directly and effectively used clinically to simulate the facial soft tissue changes in the clinical application.
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http://dx.doi.org/10.1007/s10439-015-1480-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833683PMC
May 2016

Bad split: anatomic or technical problem?

J Oral Maxillofac Surg 2015 Jun;73(6):1023-4

Houston, TX.

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http://dx.doi.org/10.1016/j.joms.2015.01.040DOI Listing
June 2015

Branchial arch syndromes.

Atlas Oral Maxillofac Surg Clin North Am 2014 Sep 15;22(2):167-73. Epub 2014 Jul 15.

Department of Oral & Maxillofacial Surgery, Houston Methodist Specialty Physician Group, Weill Medical College Cornell University, New York, 6560 Fannin Suite 1280, Houston, TX 77030, USA.

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http://dx.doi.org/10.1016/j.cxom.2014.04.003DOI Listing
September 2014

Microscopic versus open approach to craniosynostosis: a long-term outcomes comparison.

J Craniofac Surg 2014 Jul;25(4):1245-8

From the *Division of Pediatric Plastic Surgery, Department of Pediatric Surgery, The University of Texas Health Science Center at Houston, TX; †Memorial Hermann Hospital, Houston, TX; ‡Medical School, The University of Texas Health Science Center at Houston, TX; §Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital, Houston, TX; ∥Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, NY; and ¶Department of Orthodontics, The University of Texas Health Science Center at Houston, TX.

The purpose of this retrospective study was to evaluate the long-term outcomes of using the microscopic minimally invasive approach for the treatment of nonsyndromic craniosynostosis. During the last 10 years, 180 consecutive patients with nonsyndromic craniosynostosis were treated: 67 patients were treated with microscopic minimally invasive approach, and 113 were treated with the open approach. In the microscopic group, there was 1 intraoperative complication (1.5%). There were 10 postoperative complications (14.9%), of which 9 required major reoperations and 1 required a minor procedure. The major complications occurred in 7 unicoronal patients (58.3%) and 2 metopic patients (25.0%). In the open-approach group, there were 8 complications (7.1%), 2 patients required major reoperations and 6 required minor procedures. Chi-squared test showed that there was no statistically significant difference in the overall complication rate between the microscopic and open approaches. However, in the unicoronal patients, the complication rate was significantly higher in the microscopic group (P < 0.001). In conclusion, the microscopic approach is our treatment of choice in nonsyndromic patients with sagittal and lambdoidal craniosynostosis. We no longer use the microscopic approach in patients with unicoronal or metopic craniosynostosis because of the high complication rate.
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http://dx.doi.org/10.1097/SCS.0000000000000925DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4638328PMC
July 2014

Biomechanical evaluation of a new MatrixMandible plating system on cadaver mandibles.

J Oral Maxillofac Surg 2013 Nov 5;71(11):1900-14. Epub 2013 Sep 5.

Chairman, Department of Oral and Maxillofacial Surgery, The Methodist Hospital, Houston, TX; Professor of Clinical Surgery, (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, NY.

Purpose: Current mandibular plating systems contain a wide range of plates and screws needed for the treatment of mandibular reconstruction and mandibular fractures. The authors' hypothesis was that a single diameter screw could be used in all applications in a plating system. Therefore, the purpose of this study was to test if the 2.0-mm locking screws could replace the 2.4-mm screws to stabilize a 2.5-mm-thick reconstruction plate in the treatment of mandibular discontinuity.

Materials And Methods: Thirty-six fresh human cadaveric mandibles were used: 18 were plated using 2.0-mm locking screws (experimental) and the other 18 were plated using 2.4-mm locking screws (control). Each group was further divided into 3 subgroups based on the site of loading application: the ipsilateral (right) second premolar region, the central incisal region, and the contralateral (left) first molar region. The same ipsilateral (right) mandibular angular discontinuity was created by the same surgeon. The mandible was mounted on a material testing machine. The micromotions between the 2 segments, permanent and elastic displacements, were recorded after incremental ramping loads. The magnitude of screw back-out and the separation between plate and bone were recorded using a laser scanner (resolution, 0.12 mm) before and after the loading applications. The data were processed. Descriptive analyses and a general linear model for repeated measures analysis of variance were performed.

Results: There was no statistically significant difference in permanent displacement (mean, 1.16 and 0.82 mm, respectively) between the 2.0-mm and 2.4-mm screw groups. There also was no statistically significant difference in elastic displacement between the 2 groups (mean, 1.48 and 1.21 mm, respectively). Finally, there were no statistically significant differences in screw back-out or separation between plate and bone between the 2 groups. All means for screw back-out and separation between screw and bone for each group were judged within the error of the laser scanning system (<0.12 mm).

Conclusion: One may anticipate that the mechanical functions of the 2.0-mm locking screws are not different from those of the 2.4-mm screws when a 2.5-mm-thick reconstruction plate is used to reconstruct mandibular angular discontinuity. However, further biomechanical studies (ie, fatigue of screws) are warranted before a randomized clinical trial can be conducted to definitively prove that the 2.4-mm screws can be replaced by 2.0-mm screws.
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http://dx.doi.org/10.1016/j.joms.2013.06.218DOI Listing
November 2013

3D segmentation of maxilla in cone-beam computed tomography imaging using base invariant wavelet active shape model on customized two-manifold topology.

J Xray Sci Technol 2013 ;21(2):251-82

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.

Recent advances in cone-beam computed tomography (CBCT) have rapidly enabled widepsread applications of dentomaxillofacial imaging and orthodontic practices in the past decades due to its low radiation dose, high spatial resolution, and accessibility. However, low contrast resolution in CBCT image has become its major limitation in building skull models. Intensive hand-segmentation is usually required to reconstruct the skull models. One of the regions affected by this limitation the most is the thin bone images. This paper presents a novel segmentation approach based on wavelet density model (WDM) for a particular interest in the outer surface of anterior wall of maxilla. Nineteen CBCT datasets are used to conduct two experiments. This mode-based segmentation approach is validated and compared with three different segmentation approaches. The results show that the performance of this model-based segmentation approach is better than those of the other approaches. It can achieve 0.25 ± 0.2 mm of surface error from ground truth of bone surface.
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http://dx.doi.org/10.3233/XST-130369DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3735231PMC
January 2014

Incremental kernel ridge regression for the prediction of soft tissue deformations.

Med Image Comput Comput Assist Interv 2012 ;15(Pt 1):99-106

The Methodist Hospital Research Institute, Houston, Texas, USA.

This paper proposes a nonlinear regression model to predict soft tissue deformation after maxillofacial surgery. The feature which served as input in the model is extracted with finite element model (FEM). The output in the model is the facial deformation calculated from the preoperative and postoperative 3D data. After finding the relevance between feature and facial deformation by using the regression model, we establish a general relationship which can be applied to all the patients. As a new patient comes, we predict his/her facial deformation by combining the general relationship and the new patient's biomechanical properties. Thus, our model is biomechanical relevant and statistical relevant. Validation on eleven patients demonstrates the effectiveness and efficiency of our method.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3754788PMC
http://dx.doi.org/10.1007/978-3-642-33415-3_13DOI Listing
January 2013

Accuracy of a computer-aided surgical simulation protocol for orthognathic surgery: a prospective multicenter study.

J Oral Maxillofac Surg 2013 Jan 12;71(1):128-42. Epub 2012 Jun 12.

Department of Oral and Maxillofacial Surgery, The Methodist Hospital Research Institute, and Department of Pediatric Surgery, The University of Texas Health Science Center, Houston, TX 77030, USA.

Purpose: The purpose of this prospective multicenter study was to assess the accuracy of a computer-aided surgical simulation (CASS) protocol for orthognathic surgery.

Materials And Methods: The accuracy of the CASS protocol was assessed by comparing planned outcomes with postoperative outcomes of 65 consecutive patients enrolled from 3 centers. Computer-generated surgical splints were used for all patients. For the genioplasty, 1 center used computer-generated chin templates to reposition the chin segment only for patients with asymmetry. Standard intraoperative measurements were used without the chin templates for the remaining patients. The primary outcome measurements were the linear and angular differences for the maxilla, mandible, and chin when the planned and postoperative models were registered at the cranium. The secondary outcome measurements were the maxillary dental midline difference between the planned and postoperative positions and the linear and angular differences of the chin segment between the groups with and without the use of the template. The latter were measured when the planned and postoperative models were registered at the mandibular body. Statistical analyses were performed, and the accuracy was reported using root mean square deviation (RMSD) and the Bland-Altman method for assessing measurement agreement.

Results: In the primary outcome measurements, there was no statistically significant difference among the 3 centers for the maxilla and mandible. The largest RMSDs were 1.0 mm and 1.5° for the maxilla and 1.1 mm and 1.8° for the mandible. For the chin, there was a statistically significant difference between the groups with and without the use of the chin template. The chin template group showed excellent accuracy, with the largest positional RMSD of 1.0 mm and the largest orientation RMSD of 2.2°. However, larger variances were observed in the group not using the chin template. This was significant in the anteroposterior and superoinferior directions and the in pitch and yaw orientations. In the secondary outcome measurements, the RMSD of the maxillary dental midline positions was 0.9 mm. When registered at the body of the mandible, the linear and angular differences of the chin segment between the groups with and without the use of the chin template were consistent with the results found in the primary outcome measurements.

Conclusions: Using this computer-aided surgical simulation protocol, the computerized plan can be transferred accurately and consistently to the patient to position the maxilla and mandible at the time of surgery. The computer-generated chin template provides greater accuracy in repositioning the chin segment than the intraoperative measurements.
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http://dx.doi.org/10.1016/j.joms.2012.03.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3443525PMC
January 2013

New Methods to Evaluate Craniofacial Deformity and to Plan Surgical Correction.

Semin Orthod 2011 Sep;17(3):225-234

Chairman, Department of Oral and Maxillofacial Surgery, The Methodist Hospital Research Institute, Houston, TX; Professor of Clinical Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, NY; and Associate Professor, Department of Pediatric Plastic Surgery, The University of Texas Health Science Center at Houston, TX.

The success of cranio-maxillofacial (CMF) surgery depends not only on surgical techniques, but also upon an accurate surgical plan. Unfortunately, traditional planning methods are often inadequate for planning complex cranio-maxillofacial deformities. To this end, we developed 3D computer-aided surgical simulation (CASS) technique. Using our CASS method, we are able to treat patients with significant asymmetries in a single operation which in the past was usually completed in two stages. The purpose of this article is to introduce our CASS method in evaluating craniofacial deformities and planning surgical correction. In addition, we discuss the problems associated with the traditional surgical planning methods. Finally, we discuss the strength and pitfalls of using three-dimensional measurements to evaluate craniofacial deformity.
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http://dx.doi.org/10.1053/j.sodo.2011.02.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3172968PMC
September 2011

In vitro evaluation of new approach to digital dental model articulation.

J Oral Maxillofac Surg 2012 Apr 20;70(4):952-62. Epub 2011 Jul 20.

Surgical Planning Laboratory, Department of Oral and Maxillofacial Surgery, Methodist Hospital Research Institute, Houston, TX, USA.

Purpose: The purpose of the present study was to evaluate the accuracy of our newly developed approach to digital dental model articulation.

Materials And Methods: Twelve sets of stone dental models from patients with craniomaxillofacial deformities were used for validation. All the models had stable occlusion and no evidence of early contact. The stone models were hand articulated to the maximal intercuspation (MI) position and scanned using a 3-dimensional surface laser scanner. These digital dental models at the MI position served as the control group. To establish an experimental group, each mandibular dental model was disarticulated from its original MI position to 80 initial positions. Using a regular office personal computer, they were digitally articulated to the MI position using our newly developed approach. These rearticulated mandibular models served as the experimental group. Finally, the translational, rotational, and surface deviations in the mandibular position were calculated between the experimental and control groups, and statistical analyses were performed.

Results: All the digital dental models were successfully articulated. Between the control and experimental groups, the largest translational difference in mandibular position was within 0.2 mm ± 0.6 mm. The largest rotational difference was within 0.1° ± 1.1°. The averaged surface deviation was 0.08 ± 0.07. The results of the Bland and Altman method of assessing measurement agreement showed tight limits for the translational, rotational, and surface deviations. In addition, the final positions of the mandibular articulated from the 80 initial positions were absolutely agreed on.

Conclusion: The results of our study have demonstrated that using our approach, the digital dental models can be accurately and effectively articulated to the MI position. In addition, the 3-dimensional surface geometry of the mandibular teeth played a more important role in digital dental articulation than the initial position of the mandibular teeth.
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http://dx.doi.org/10.1016/j.joms.2011.02.109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4638325PMC
April 2012

Outcome study of computer-aided surgical simulation in the treatment of patients with craniomaxillofacial deformities.

J Oral Maxillofac Surg 2011 Jul;69(7):2014-24

Department of Oral and Maxillofacial Surgery, Methodist Hospital Research Institute, Houston, TX 77030, USA.

Purpose: The purpose of this study was to determine whether the surgical outcomes achieved with computer-aided surgical simulation (CASS) are better than those achieved with traditional methods.

Materials And Methods: Twelve consecutive patients with craniomaxillofacial (CMF) deformities were enrolled. According to the CASS clinical protocol, a 3-dimensional computer composite skull model for each patient was generated and reoriented to the neutral head posture. These models underwent 2 virtual surgeries: 1 was based on CASS (experimental group) and the other was based on traditional methods 1 year later (control group). Once the 2 virtual surgeries were completed, 2 experienced oral and maxillofacial surgeons at 2 different settings evaluated the 2 surgical outcomes. They were blinded to the planning method used on the virtual models and each other's evaluation results. The primary outcome was overall CMF skeletal harmony. The secondary outcomes were individual maxillary, mandibular, and chin harmonies. Statistical analyses were performed.

Results: Overall CMF skeletal harmony achieved with CASS was statistically significantly better than that achieved with traditional methods. In addition, the maxillary and mandibular surgical outcomes achieved with CASS were significantly better. Furthermore, although not included in the statistical model, the chin symmetry achieved by CASS tended to be better. A regression model was established between mandibular symmetry and overall CMF skeletal harmony.

Conclusion: The surgical outcomes achieved with CASS are significantly better than those achieved with traditional planning methods. In addition, CASS enables the surgeon to better correct maxillary yaw deformity, better place proximal/distal segments, and better restore mandibular symmetry. The critical step in achieving better overall CMF skeletal harmony is to restore mandibular symmetry.
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http://dx.doi.org/10.1016/j.joms.2011.02.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3119456PMC
July 2011

Effect of facial asymmetry on 2-dimensional and 3-dimensional cephalometric measurements.

J Oral Maxillofac Surg 2011 Mar;69(3):655-62

Department of Oral and Maxillofacial Surgery, Methodist Hospital, Houston, TX 77030, USA.

Purpose: To test the hypothesis that facial symmetry affects both 2-dimensional (2D) and 3-dimensional (3D) cephalometric measurements.

Methods: A baseline model of a preferred symmetrical face was first constructed. It consisted of a set of commonly used cephalometric landmarks. Seven cephalometric measurements were selected for testing. Each of them represented a different set of geometrical conditions related to the geometric parameters being measured, the elements involved, and the type of measurements. They served as a control group. The baseline model was then modified to simulate 10 different asymmetric models, 6 with maxillary asymmetries and 4 with mandibular asymmetries. The same 7 cephalometric analysis were utilized again on each of the 10 asymmetric models. They served as an experimental group.

Results: The resulted measurements were tabulated and compared. For the measurements of shape, the 2D cephalometric measurement was distorted by roll and yaw asymmetries, while the same measurement in 3D was not. For the measurements of size, the 2D measurement was also distorted by yaw, but not by roll, while again this measurement in 3D was not distorted. For measurements of position, the results were reversed. The 2D cephalometric measurements of position were not distorted, while all measurements in 3D were distorted. Of note, the magnitude of the distortion was much larger for the linear measurement than angular measurement. Finally, measurements of orientation, both 2D and 3D measurements were distorted by asymmetry, although the magnitude of the distortion was larger for the 3D measurements.

Conclusion: This study confirmed the hypothesis that facial asymmetry affects both 2D and 3D cephalometric measurements. It also demonstrated that the effects of asymmetry on cephalometric measurements depend on the geometric parameter being measured (ie, shape, size, position, or orientation).
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http://dx.doi.org/10.1016/j.joms.2010.10.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3179273PMC
March 2011