Automated tooth crown design with optimized shape and biomechanics properties

Despite the large demand for dental restoration each year, the design of crown restorations is mainly performed via manual software operation, which is tedious and subjective. Moreover, the current design process lacks biomechanics optimization, leading to localized stress concentration and reduced working life. To tackle these challenges, we develop a fully automated algorithm for crown restoration based on deformable model fitting and biomechanical optimization. From a library of dental oral scans, a conditional shape model (CSM) is constructed to represent the inter-teeth shape correlation. By matching the CSM to the patient’s oral scan, the optimal crown shape is estimated to coincide with the surrounding teeth. Next, the crown is seamlessly integrated into the finish line of preparation via a surface warping step. Finally, porous internal supporting structures of the crown are generated to avoid excessive localized stresses. This algorithm is validated on clinical oral scan data and achieved less than 2 mm mean surface distance as compared to the manual designs of experienced human operators. The mechanical simulation was conducted to prove that the internal supporting structures lead to uniform stress distribution all over the model

Biomechanics of Contemporary Implants and Prosthesis: Modeling, Experiments, and Clinical Application

Modern medicine is now more oriented towards patient-based treatments. Taking into account individual biological features allows for increasing the quality of the healing process. Opportunities for modern hardware and software allow not only the complex behavior of implants and prostheses to be simulated, but also take into account any peculiarities of the patient. Moreover, the development of additive manufacturing expands the opportunities for materials. Technical limits for composite materials, biomaterials, and metamaterials are decreasing. On the other hand, there is a need for more detailed analyses of biomechanics research. A deeper understanding of the technological processes of implants, and the mechanobiological interactions of implants and organisms will potentially allow us to raise the level of medical treatment. Modern trends of the biomechanics of contemporary implants and prostheses, including experimental and mathematical modeling and clinical application, are discussed in this book

Effect of the interface geometry on the structural integrity of the ceramic crown-tooth complex

The effect of the interface lute on the structural integrity of the tooth adhesively restored with an all-ceramic crown remains is an unknown parameter especially in relation to the interface geometry (thickness and uniformity). Traditionally, the structural integrity of a restored tooth system (tooth-lute-crown) is tested by laboratory based mechanical testing. However, a more sophisticated FEA computer modelling seems to provide a non-destructive way of understanding the structural integrity of the system, which may complement mechanical testing

Computational Modeling of Fracture Failure in Mineralized and Prosthetic Biomaterials

Natural mineralized tissues, e.g., teeth and bone, have the capacity to tolerate the daily physiological loading. However, due to their high mineralized composition, they have been recognized as a class of relatively brittle biomaterials. The inherent brittle nature and fairly high susceptibility to mechanical failure present a more critical problem in biomedical research field. To replace such diseased or damaged mineralized tissues, prosthetic materials are largely applied in the areas of dental and osteo clinical treatments. Ceramic materials provide numerous favourable characteristics, including biocompatibility and chemical resistance. In addition to the dental industry, applications of osteofixation/osteosynthiesis devices are considered fundamental to stabilize various treatments of bone defects for promoting osteointegration and reconstruction. However, clinical observations and specialized literature have revealed that dental restorative materials and prosthetic fixation devices are often subject to high stress, leading to fracture either by catastrophic overloading or cyclic fatigue failure. The aim of this thesis is to develop a computational modelling framework on the basis of the extended finite element method (XFEM) to investigate the fracture behaviors of mineralised and synthetic biomaterials in various medical applications. The XFEM modelling results are validated by being compared with the in-vitro experiments and/or clinical observations. Through the research in this thesis studies, XFEM has been demonstrated to be a powerful tool to analyse fracture behaviors in the bio-structures subjected to not only static loadings but also cyclic loadings. The outcomes generated in this thesis help gain some insightful understanding failure of the native or prosthetic structures, which is anticipated to provide some clinical guidelines for the design optimisation of patient-specific prosthetic devices to ensure their reliability and longevity

Unveiling the prospects of point-of-care 3D printing of Polyetheretherketone (PEEK) patient-specific implants

Additive manufacturing (AM) or three-dimensional (3D) printing is rapidly gaining acceptance in the healthcare sector. With the availability of low-cost desktop 3D printers and inexpensive materials, in-hospital or point-of-care (POC) manufacturing has gained considerable attention in personalized medicine. Material extrusion-based [Fused Filament Fabrication (FFF)] 3D printing of low-temperature thermoplastic polymer is the most commonly used 3D printing technology in hospitals due to its ease of operability and availability of low-cost machines. However, this technology has been limited to the production of anatomical biomodels, surgical guides, and prosthetic aids and has not yet been adopted into the mainstream production of patient-specific or customized implants. Polyetheretherketone (PEEK), a high-performance thermoplastic polymer, has been used mainly in reconstructive surgeries as a reliable alternative to other alloplastic materials to fabricate customized implants. With advancements in AM systems, prospects for customized 3D printed surgical implants have emerged, increasing attention for POC manufacturing. A customized implant may be manufactured within few hours using 3D printing, allowing hospitals to become manufacturers. However, manufacturing customized implants in a hospital environment is challenging due to the number of actions necessary to design and fabricate the implants. The focus of this thesis relies on material extrusion-based 3D printing of PEEK patient-specific implants (PSIs). The ambitious challenge was to bridge the performance gap between 3D printing of PEEK PSIs for reconstructive surgery and the clinical applicability at the POC by taking advantage of recent developments in AM systems. The main reached milestones of this project include: (i) assessment of the fabrication feasibility of PEEK surgical implants using material extrusion-based 3D printing technology, (ii) incorporation of a digital clinical workflow for POC manufacturing, (iii) assessment of the clinical applicability of the POC manufactured patient-specific PEEK scaphoid prosthesis, (iv) visualization and quantification of the clinical reliability of the POC manufactured patient-specific PEEK cranial implants, and (v) assessment of the clinical performance of the POC manufactured porous patient-specific PEEK orbital implants. During this research work, under the first study, we could demonstrate the prospects of FFF 3D printing technology for POC PEEK implant manufacturing. It was established that FFF 3D printing of PEEK allows the construction of complex anatomical geometries which cannot be manufactured using other technologies. With a clinical digital workflow implementation at the POC, we could further illustrate a smoother integration and faster implant production (within two hours) potential for a complex-shaped, patented PEEK patient-specific scaphoid prosthesis. Our results revealed some key challenges during the FFF printing process, exploring the applicability of POC manufactured FFF 3D printed PEEK customized implants in craniofacial reconstructions. It was demonstrated that optimal heat distribution around the cranial implants and heat management during the printing process are essential parameters that affect crystallinity, and thus the quality of the FFF 3D printed PEEK cranial implants. At this stage of the investigation, it was observed that the root mean square (RMS) values for dimensional accuracy revealed higher deviations in large-sized cranial prostheses with “horizontal lines” characteristics. Further optimization of the 3D printer, a layer-by-layer increment in the airflow temperature was done, which improved the performance of the FFF PEEK printing process for large-sized cranial implants. We then evaluated the potential clinical reliability of the POC manufactured 3D printed PEEK PSIs for cranial reconstruction by quantitative assessment of geometric, morphological, and biomechanical characteristics. It was noticed that the 3D printed customized cranial implants had high dimensional accuracy and repeatability, displaying clinically acceptable morphologic similarity concerning fit and contours continuity. However, the tested cranial implants had variable peak load values with discrete fracture patterns from a biomechanical standpoint. The implants with the highest peak load had a strong bonding with uniform PEEK fusion and interlayer connectivity, while air gaps and infill fusion lines were observed in implants with the lowest strength. The results of this preclinical study were in line with the clinical applicability of cranial implants; however, the biomechanical attribute can be further improved. It was noticed that each patient-specific reconstructive implant required a different set of manufacturing parameters. This was ascertained by manufacturing a porous PEEK patient-specific orbital implant. We evaluated the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the design variants, biomechanical, and morphological parameters. We then studied the performance of the implants as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predicted the high durability of the implants. In all the implant profile configurations, the maximum deformation values were under one-tenth of a millimeter (mm) domain. The circular patterned design variant implant revealed the best performance score. The study further demonstrated that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor. In the framework of the current thesis, the potential clinical application of material extrusion-based 3D printing for PEEK customized implants at the POC was demonstrated. We implemented clinical experience and engineering principles to generate a technical roadmap from preoperative medical imaging datasets to virtual surgical planning, computer-aided design models of various reconstructive implant variants, to the fabrication of PEEK PSIs using FFF 3D printing technology. The integration of 3D printing PEEK implants at the POC entails numerous benefits, including a collaborative team approach, quicker turnaround time of customized implants, support in pre-surgical and intraoperative planning, improved patient outcomes, and decreased overall healthcare cost. We believe that FFF 3D printing of customized PEEK implants could become an integral part of the hospitals and holds potential for various reconstructive surgery applications

a digital workflow for an implant retained over denture a new approach

n/

Phenomenological modeling of image irradiance for non-Lambertian surfaces under natural illumination.

Various vision tasks are usually confronted by appearance variations due to changes of illumination. For instance, in a recognition system, it has been shown that the variability in human face appearance is owed to changes to lighting conditions rather than person\u27s identity. Theoretically, due to the arbitrariness of the lighting function, the space of all possible images of a fixed-pose object under all possible illumination conditions is infinite dimensional. Nonetheless, it has been proven that the set of images of a convex Lambertian surface under distant illumination lies near a low dimensional linear subspace. This result was also extended to include non-Lambertian objects with non-convex geometry. As such, vision applications, concerned with the recovery of illumination, reflectance or surface geometry from images, would benefit from a low-dimensional generative model which captures appearance variations w.r.t. illumination conditions and surface reflectance properties. This enables the formulation of such inverse problems as parameter estimation. Typically, subspace construction boils to performing a dimensionality reduction scheme, e.g. Principal Component Analysis (PCA), on a large set of (real/synthesized) images of object(s) of interest with fixed pose but different illumination conditions. However, this approach has two major problems. First, the acquired/rendered image ensemble should be statistically significant vis-a-vis capturing the full behavior of the sources of variations that is of interest, in particular illumination and reflectance. Second, the curse of dimensionality hinders numerical methods such as Singular Value Decomposition (SVD) which becomes intractable especially with large number of large-sized realizations in the image ensemble. One way to bypass the need of large image ensemble is to construct appearance subspaces using phenomenological models which capture appearance variations through mathematical abstraction of the reflection process. In particular, the harmonic expansion of the image irradiance equation can be used to derive an analytic subspace to represent images under fixed pose but different illumination conditions where the image irradiance equation has been formulated in a convolution framework. Due to their low-frequency nature, irradiance signals can be represented using low-order basis functions, where Spherical Harmonics (SH) has been extensively adopted. Typically, an ideal solution to the image irradiance (appearance) modeling problem should be able to incorporate complex illumination, cast shadows as well as realistic surface reflectance properties, while moving away from the simplifying assumptions of Lambertian reflectance and single-source distant illumination. By handling arbitrary complex illumination and non-Lambertian reflectance, the appearance model proposed in this dissertation moves the state of the art closer to the ideal solution. This work primarily addresses the geometrical compliance of the hemispherical basis for representing surface reflectance while presenting a compact, yet accurate representation for arbitrary materials. To maintain the plausibility of the resulting appearance, the proposed basis is constructed in a manner that satisfies the Helmholtz reciprocity property while avoiding high computational complexity. It is believed that having the illumination and surface reflectance represented in the spherical and hemispherical domains respectively, while complying with the physical properties of the surface reflectance would provide better approximation accuracy of image irradiance when compared to the representation in the spherical domain. Discounting subsurface scattering and surface emittance, this work proposes a surface reflectance basis, based on hemispherical harmonics (HSH), defined on the Cartesian product of the incoming and outgoing local hemispheres (i.e. w.r.t. surface points). This basis obeys physical properties of surface reflectance involving reciprocity and energy conservation. The basis functions are validated using analytical reflectance models as well as scattered reflectance measurements which might violate the Helmholtz reciprocity property (this can be filtered out through the process of projecting them on the subspace spanned by the proposed basis, where the reciprocity property is preserved in the least-squares sense). The image formation process of isotropic surfaces under arbitrary distant illumination is also formulated in the frequency space where the orthogonality relation between illumination and reflectance bases is encoded in what is termed as irradiance harmonics. Such harmonics decouple the effect of illumination and reflectance from the underlying pose and geometry. Further, a bilinear approach to analytically construct irradiance subspace is proposed in order to tackle the inherent problem of small-sample-size and curse of dimensionality. The process of finding the analytic subspace is posed as establishing a relation between its principal components and that of the irradiance harmonics basis functions. It is also shown how to incorporate prior information about natural illumination and real-world surface reflectance characteristics in order to capture the full behavior of complex illumination and non-Lambertian reflectance. The use of the presented theoretical framework to develop practical algorithms for shape recovery is further presented where the hitherto assumed Lambertian assumption is relaxed. With a single image of unknown general illumination, the underlying geometrical structure can be recovered while accounting explicitly for object reflectance characteristics (e.g. human skin types for facial images and teeth reflectance for human jaw reconstruction) as well as complex illumination conditions. Experiments on synthetic and real images illustrate the robustness of the proposed appearance model vis-a-vis illumination variation. Keywords: computer vision, computer graphics, shading, illumination modeling, reflectance representation, image irradiance, frequency space representations, {hemi)spherical harmonics, analytic bilinear PCA, model-based bilinear PCA, 3D shape reconstruction, statistical shape from shading

Mechanical Properties of Materials

In the oral environment, restorative and prosthetic materials and appliances are exposed to chemical, thermal and mechanical challenges. The mechanical properties of a material define how it responds to the application of a physical force. Recent advances in nanotechnology and 3D printing have rapidly spread, and manufacturers continuously develop new materials and solutions to provide high-quality dental care, with particular attention being paid to long-term follow-up. Restorative dentistry, prosthodontics, oral surgery, implants, periodontology and orthodontics are all involved in this continuing evolution. This Special Issue focuses on all the recent technology that can enhance the mechanical properties of materials used in all of the different branches of dentistry