A pilot study for the digital replacement of a distorted dentition acquired by Cone Beam Computed Tomography (CBCT)

Abstract Introduction: Cone beam CT (CBCT) is becoming a routine imaging modality designed for the maxillofacial region. Imaging patients with intra-oral metallic objects cause streak artefacts. Artefacts impair any virtual model by obliterating the teeth. This is a major obstacle for occlusal registration and the fabrication of orthognathic wafers to guide the surgical correction of dentofacial deformities. Aims and Objectives: To develop a method of replacing the inaccurate CBCT images of the dentition with an accurate representation and test the feasibility of the technique in the clinical environment. Materials and Method: Impressions of the teeth are acquired and acrylic baseplates constructed on dental casts incorporating radiopaque registration markers. The appliances are fitted and a preoperative CBCT is performed. Impressions are taken of the dentition with the devices in situ and subsequent dental models produced. The models are scanned to produce a virtual model. Both images of the patient and the model are imported into a virtual reality software program and aligned on the virtual markers. This allows the alignment of the dentition without relying on the teeth for superimposition. The occlusal surfaces of the dentition can be replaced with the occlusal image of the model. Results: The absolute mean distance of the mesh between the markers in the skulls was in the region of 0.09mm ± 0.03mm; the replacement dentition had an absolute mean distance of about 0.24mm ± 0.09mm. In patients the absolute mean distance between markers increased to 0.14mm ± 0.03mm. It was not possible to establish the discrepancies in the patient’s dentition, since the original image of the dentition is inherently inaccurate. Conclusion: It is possible to replace the CBCT virtual dentition of cadaveric skulls with an accurate representation to create a composite skull. The feasibility study was successful in the clinical arena. This could be a significant advancement in the accuracy of surgical prediction planning, with the ultimate goal of fabrication of a physical orthognathic wafer using reverse engineering

Survey of Finite Element Method-Based Real-Time Simulations

The finite element method (FEM) has deservedly gained the reputation of the most powerful, highly efficient, and versatile numerical method in the field of structural analysis. Though typical application of FE programs implies the so-called “off-line” computations, the rapid pace of hardware development over the past couple of decades was the major impetus for numerous researchers to consider the possibility of real-time simulation based on FE models. Limitations of available hardware components in various phases of developments demanded remarkable innovativeness in the quest for suitable solutions to the challenge. Different approaches have been proposed depending on the demands of the specific field of application. Though it is still a relatively young field of work in global terms, an immense amount of work has already been done calling for a representative survey. This paper aims to provide such a survey, which of course cannot be exhaustive

The virtual human face – superimposing the simultaneously captured 3D photorealistic skin surface of the face on the untextured skin image of the CBCT Scan

The aim of this study was to evaluate the impact of simultaneous capture of the three-dimensional (3D) surface of the face and cone beam computed tomography (CBCT) scan of the skull on the accuracy of their registration and superimposition. 3D facial images were acquired in 14 patients using the Di3d (Dimensional Imaging, UK) imaging system and i-CAT CBCT scanner. One stereophotogrammetry image was captured at the same time as the CBCT and another one hour later. The two stereophotographs were then individually superimposed over the CBCT using VRmesh. Seven patches were isolated on the final merged surfaces. For the whole face and each individual patch; maximum and minimum range of deviation between surfaces, absolute average distance between surfaces, and standard deviation for the 90th percentile of the distance errors were calculated. The superimposition errors of the whole face for both captures revealed statistically significant differences (P=0.00081). The absolute average distances in both separate and simultaneous captures were 0.47mm and 0.27mm, respectively. The level of superimposition accuracy in patches from separate captures ranged between 0.3 and 0.9mm, while that of simultaneous captures was 0.4mm. Simultaneous capture of Di3d and CBCT images significantly improved the accuracy of superimposition of these image modalities

Biomechanics and Remodelling for Design and Optimisation in Oral Prosthesis and Therapeutical Procedure

The purpose of dental prostheses is to restore the oral function for edentulous patients. Introducing any dental prosthesis into mouth will alter biomechanical status of the oral environment, consequently inducing bone remodelling. Despite the advantageous benefits brought by dental prostheses, the attendant clinical complications and challenges, such as pain, discomfort, tooth root resorption, and residual ridge reduction, remain to be addressed. This thesis aims to explore several different dental prostheses by understanding the biomechanics associated with the potential tissue responses and adaptation, and thereby applying the new knowledge gained from these studies to dental prosthetic design and optimisation. Within its biomechanics focus, this thesis is presented in three major clinical areas, namely prosthodontics, orthodontics and dental implantology. In prosthodontics, the oral mucosa plays a critical role in distributing occlusal forces a denture to the underlying bony structure, and its response is found in a complex, dynamic and nonlinear manner. It is discovered that interstitial fluid pressure in mocosa is the most important indicator to the potential resorption induced by prosthetic denture insertion, and based on this finding, patient-specific analysis is performed to investigate the effects caused by various types of dentures and prediction of the bone remodelling activities. In orthodontic treatments, a dynamic algorithm is developed to analyse and predict potential bone remodelling around the target tooth during orthodontic treatment, thereby providing a numerical approach for treatment planning. In dental implantology, a graded surface morphology of an implant is designed to improve osseointegration over that of a smooth uniform surface in both the short and long term. The graded surface can be optimised to achieve the best possible balance between the bone-implant contact and the peak Tresca stress for the specific clinical application need

3D-Guided Face Manipulation of 2D Images for the Prediction of Post-Operative Outcome after Cranio-Maxillofacial Surgery

Cranio-maxillofacial surgery often alters the aesthetics of the face which can be a heavy burden for patients to decide whether or not to undergo surgery. Today, physicians can predict the post-operative face using surgery planning tools to support the patient\u27s decision-making. While these planning tools allow a simulation of the post-operative face, the facial texture must usually be captured by another 3D texture scan and subsequently mapped on the simulated face. This approach often results in face predictions that do not appear realistic or lively looking and are therefore ill-suited to guide the patient\u27s decision-making. Instead, we propose a method using a generative adversarial network to modify a facial image according to a 3D soft-tissue estimation of the post-operative face. To circumvent the lack of available data pairs between pre- and post-operative measurements we propose a semi-supervised training strategy using cycle losses that only requires paired open-source data of images and 3D surfaces of the face\u27s shape. After training on "in-the-wild" images we show that our model can realistically manipulate local regions of a face in a 2D image based on a modified 3D shape. We then test our model on four clinical examples where we predict the post-operative face according to a 3D soft-tissue prediction of surgery outcome, which was simulated by a surgery planning tool. As a result, we aim to demonstrate the potential of our approach to predict realistic post-operative images of faces without the need of paired clinical data, physical models, or 3D texture scans

CBCT imaging – A boon to orthodontics

AbstractThe application of innovative technologies in dentistry and orthodontics has been very interesting to observe. The development of cone-beam computed tomography (CBCT) as a preferred imaging procedure for comprehensive orthodontic treatment is of particular interest. The information obtained from CBCT imaging provides several substantial advantages. For example, CBCT imaging provides accurate measurements, improves localization of impacted teeth, provides visualization of airway abnormalities, it identifies and quantifies asymmetry, it can be used to assess periodontal structures, to identify endodontic problems, to plan placement sites for temporary skeletal anchorage devices, and to view condylar positions and temporomandibular joint (TMJ) bony structures according to the practitioner’s knowledge at the time of orthodontic diagnosis. Moreover, CBCT imaging involves only a minimal increase in radiation dose relative to combined diagnostic modern digital panoramic and cephalometric imaging. The aim of this article is to provide a comprehensive overview of CBCT imaging, including its technique, advantages, and applications in orthodontics

How to Obtain an Orthodontic Virtual Patient through Superimposition of Three-Dimensional Data: A Systematic Review

Background: This systematic review summarizes the current knowledge on the superimposition of three-dimensional (3D) diagnostic records to realize an orthodontic virtual patient. The aim of this study is to analyze the accuracy of the state-of-the-art digital workflow. Methods: The research was carried out by an electronic and manual query eectuated from ISS (Istituto Superiore di Sanit\ue0 in Rome) on three dierent databases (MEDLINE, Cochrane Library and ISI WEB OF SCIENCE) up to 31st January 2020. The search focused on studies that superimposed at least two dierent 3D records to build up a 3D virtual patient\u2014information about the devices used to acquire 3D data, the software used to match data and the superimposition method applied have been summarized. Results: 1374 titles were retrieved from the electronic search. After title-abstract screening, 65 studies were selected. After full-text analysis, 21 studies were included in the review. Dierent 3D datasets were used: facial skeleton (FS), extraoral soft tissues (ST) and dentition (DENT). The information provided by the 3D data was superimposed in four dierent combinations: FS + DENT (13 papers), FS + ST (5 papers), ST + DENT (2 papers) and all the types (FS + ST + DENT) (1 paper). Conclusions: The surface-based method was most frequently used for 3D objects superimposition (11 papers), followed by the point-based method (6 papers), with or without fiducial markers, and the voxel-based method (1 paper). Most of the papers analyzed the accuracy of the superimposition procedure (15 papers), while the remaining were proof-of-principles (10 papers) or compared dierent methods (3 papers). Further studies should focus on the definition of a gold standard. The patient is going to have a huge advantage from complete digital planning when more information about the spatial relationship of anatomical structures are needed: ectopic, impacted and supernumerary teeth, root resorption and angulations, cleft lip and palate (CL/P), alveolar boundary conditions, periodontally compromised patients, temporary anchorage devices (TADs), maxillary transverse deficiency, airway analyses, obstructive sleep apnea (OSAS), TMJ disorders and orthognathic and cranio-facial surgery

Computer aided modelling to simulate the biomechanical behaviour of customised orthodontic removable appliances

In the field of orthodontics, the use of Removable Thermoplastic Appliances (RTAs) to treat moderate malocclusion problems is progressively replacing traditional fixed brackets. Generally, these orthodontic devices are designed on the basis of individual anatomies and customised requirements. However, many elements may affect the effectiveness of a RTA-based therapy: accuracies of anatomical reference models, clinical treatment strategies, shape features and mechanical properties of the appliances. In this paper, a numerical model for customised orthodontic treatments planning is proposed by means of the finite element method. The model integrates individual patient’s teeth, periodontal ligaments, bone tissue with structural and geometrical attributes of the appliances. The anatomical tissues are reconstructed by a multi-modality imaging technique, which combines 3D data obtained by an optical scanner (visible tissues) and a computerised tomography system (internal tissues). The mechanical interactions between anatomical shapes and appliance models are simulated through finite element analyses. The numerical approach allows a dental technician to predict how the RTA attributes affect tooth movements. In this work, treatments considering rotation movements for a maxillary incisor and a maxillary canine have been analysed by using multi-tooth models

Physical and statistical shape modelling in craniomaxillofacial surgery: a personalised approach for outcome prediction

Orthognathic surgery involves repositioning of the jaw bones to restore face function and shape for patients who require an operation as a result of a syndrome, due to growth disturbances in childhood or after trauma. As part of the preoperative assessment, three-dimensional medical imaging and computer-assisted surgical planning help to improve outcomes, and save time and cost. Computer-assisted surgical planning involves visualisation and manipulation of the patient anatomy and can be used to aid objective diagnosis, patient communication, outcome evaluation, and surgical simulation. Despite the benefits, the adoption of three-dimensional tools has remained limited beyond specialised hospitals and traditional two-dimensional cephalometric analysis is still the gold standard. This thesis presents a multidisciplinary approach to innovative surgical simulation involving clinical patient data, medical image analysis, engineering principles, and state-of-the-art machine learning and computer vision algorithms. Two novel three-dimensional computational models were developed to overcome the limitations of current computer-assisted surgical planning tools. First, a physical modelling approach – based on a probabilistic finite element model – provided patient-specific simulations and, through training and validation, population-specific parameters. The probabilistic model was equally accurate compared to two commercial programs whilst giving additional information regarding uncertainties relating to the material properties and the mismatch in bone position between planning and surgery. Second, a statistical modelling approach was developed that presents a paradigm shift in its modelling formulation and use. Specifically, a 3D morphable model was constructed from 5,000 non-patient and orthognathic patient faces for fully-automated diagnosis and surgical planning. Contrary to traditional physical models that are limited to a finite number of tests, the statistical model employs machine learning algorithms to provide the surgeon with a goal-driven patient-specific surgical plan. The findings in this thesis provide markers for future translational research and may accelerate the adoption of the next generation surgical planning tools to further supplement the clinical decision-making process and ultimately to improve patients’ quality of life