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OBJECTIVES Chronic liver disease increases the risk for periodontal disease and osteoporotic fractures, but its impacts on bone regeneration remain unknown. Herein, we studied the impact of liver cirrhosis on peri-implant bone formation. MATERIAL AND METHODS A total of 20 male Wistar rats were randomly divided into two groups: one with the common bile duct ligated (BDL) and the respective sham-treated control group (SHAM). After four weeks of disease induction, titanium mini-screws were inserted into the tibia. Successful induction of liver cirrhosis was confirmed by the presence of clinical symptoms. Another four weeks later, peri-implant bone volume per tissue volume (BV/TV) and bone-to-implant contact (BIC) were determined by histomorphometric analysis. RESULTS Peri-implant bone formation was not significantly different between the SHAM and BDL groups. In the cortical compartment, the median percentage of peri-implant new bone was 10.1% (95% CI of mean 4.0-35.7) and 22.5% (13.8-30.6) in the SHAM and BDL groups, respectively (p��=��.26). Consistently, the new bone in direct contact with the implant was 18.1% (0.4-37.8) and 23.3% (9.2-32.8) in SHAM and BDL groups, respectively (p��=��.38). When measuring the medullary compartment, the new bone area was 7.1% (4.8-10.4) and 10.4% (7.2-13.5) in the SHAM and BDL groups, respectively (p��=��.17). Medullary new bone in direct contact with the implant was 10.0% (1.2-50.4) and 20.6% (16.8-35.3) in SHAM and BDL groups, respectively, and thus comparable between the two groups (p��=��.46). CONCLUSIONS Bile duct ligation has no significant impact on the early stages of peri-implant bone formation.

Sleep bruxism is an oral parafunction that involves involuntary tooth grinding and clenching. Splints with a colored layer that gets removed during tooth grinding are a common tool for the initial diagnosis of sleep bruxism. Currently, such splints are either assessed qualitatively or using 2D photographs, leading to a non-neglectable error due to the 3D nature of the dentition. In this study we propose a new and fast method for the quantitative assessment of tooth grinding surfaces using 3D scanning and mesh processing. We assessed our diagnostic method by producing 18 standardized splints with 8 grinding surfaces each, giving us a total of 144 surfaces. Moreover, each splint was scanned and analyzed five times. The accuracy and repeatability of our method was assessed by computing the intraclass correlation coefficient (ICC) as well reporting means and standard deviations of surface measurements for intra- and intersplint measurements. An ICC of 0.998 was computed as well as a maximum standard deviation of 0.63 mm2 for repeated measures, suggesting an appropriate accuracy of our proposed method. Overall, this study proposes an innovative, fast and cost effective method to support the initial diagnosis of sleep bruxism.

Objective: Musculoskeletal simulation can be used to estimate muscle forces in clinical movement studies. However, such simulations typically only target movement measurements and are not applicable to force exertion tasks which are commonly used in rehabilitation therapy. Simulations can also produce nonphysiological joint forces or be too slow for real-time clinical applications, such as rehabilitation with real-time feedback. The objective of this study is to propose and evaluate a new formulation of forward-dynamics assisted tracking simulation that incorporates measured reaction forces as targets or constraints without any additional computational cost. Methods: We illustrate our method with idealized proof-of-concept models and evaluate it with two upper limb cases: Tracking of hand reaction forces during an isometric force-generation task and constraining glenohumeral joint reaction forces for stability during arm elevation. Results: We show that the addition of reaction force optimization terms within our simulations generates plausible muscle force predictions for these tasks, which are strongly related to reaction forces in addition to movement. Execution times for all models tested were not different when run with or without the reaction force optimization term, ensuring that the simulations are fast enough for real-time clinical applications. Conclusion: Our novel reaction force optimization term leads to more realistic shoulder reaction forces, without any additional computational costs. Significance: Our formulation is not only valuable for shoulder simulations, but could be used in various clinical situations (e.g., for different joints and rehabilitation therapy tasks) where the direction and/or magnitude of reaction forces are of interest.

This study aimed to address the predictive value of a micro-computed tomography (μCT)-based finite element (μFE) model of a human cadaveric edentulous posterior mandible, rehabilitated by short dental implants. Hereby, three different prosthetic/implant configurations of fixed partial dentures ("Sp"-3 splinted crowns on 3 implants, "Br" - Bridge: 3 splinted crowns on 2 implants, and "Si"- 3 single crowns) were analysed by comparing the computational predictions of the global stiffness with experimental data.Experimental displacement of the bone/implant/prosthesis system was measured under axial and oblique loads of 100 N using an optical deformation system (GOM Aramis) and the overall movement of the testing machine (Zwick Z030). Together with the measured machine force, an "Aramis" (optical markers) and "Zwick" (test machine) stiffness were calculated. FE models were created based on μCT-scans of the cadaveric mandible sample (n = 1) before and after implantation and using stl-files of the crowns. The same load tests and boundary conditions were simulated on the models and the μFE-results were compared to experimental data using linear regression analysis.The regression line through a plot of pooled stiffness values (N/mm) for the optical displacement recording (true local displacement) and the test machine (machine compliance included) had a slope of 0.57 and a correlation coefficient RThe current study showed good qualitative agreement between the experimental and predicted global stiffness of different short implant configurations. It could be deduced that 1:1 splinting of the short implants by the crowns is most favorable for the stiffness of the implant/prosthesis system. However, in the clinical context, the absolute in silico readings must be interpreted cautiously, as the FEA showed a considerable overestimation of the values.

Mastication is the motor task with the highest muscle activations of the jaw region, potentially leading to high temporomandibular joint (TMJ) loading. Since increased loading of the TMJ is associated with temporomandibular disorders (TMD), TMJ mechanics during chewing has potential clinical relevance in TMD treatment. TMD self-management guidelines suggest eating soft and small pieces of food to reduce TMJ pain. Since TMJ loading cannot be measured in vivo, due to patient safety restrictions, computer modeling is an important tool for investigations of the potential connection between TMJ loading and TMD. The objective of this study is to investigate the effect of food bolus variables on mechanical TMJ loading to help inform better self-management guidelines for TMD. A combined rigid-body-finite-element model of the jaw region was used to investigate the effect of bolus size, stiffness, and position. Mandibular motion and TMJ disc von Mises stress were reported. Computed mandibular motion generally agrees well with previous literature. Disc stress was higher during the closing phase of the chewing cycle and for the non-working side disc. Smaller and softer food boluses overall lead to less TMJ loading. The results reinforce current guidelines regarding bolus modifications and provide new potential guidelines for bolus positioning that could be verified through a future clinical trial. The paper presents a first in silico investigation of dynamic chewing with detailed TMJ stress for different bolus properties. The results help to strengthen the confidence in TMD self-management recommendations, potentially reducing pain levels of patients.

The masticatory region is an important human motion system that is essential for basic human tasks like mastication, speech or swallowing. An association between temporomandibular disorders (TMDs) and high temporomandibular joint (TMJ) stress has been suggested, but in vivo joint force measurements are not feasible to directly test this assumption. Consequently, biomechanical computer simulation remains as one of a few means to investigate this complex system. To thoroughly examine orofacial biomechanics, we developed a novel, dynamic computer model of the masticatory system. The model combines a muscle driven rigid body model of the jaw region with a detailed finite element model (FEM) disk and elastic foundation (EF) articular cartilage. The model is validated using high-resolution MRI data for protrusion and opening that were collected from the same volunteer. Joint stresses for a clenching task as well as protrusive and opening movements are computed. Simulations resulted in mandibular positions as well as disk positions and shapes that agree well with the MRI data. The model computes reasonable disk stress patterns for dynamic tasks. Moreover, to the best of our knowledge this model presents the first ever contact model using a combination of EF layers and a FEM body, which results in a clear decrease in computation time. In conclusion, the presented model is a valuable tool for the investigation of the human TMJ and can potentially help in the future to increase the understanding of the masticatory system and the relationship between TMD and joint stress and to highlight potential therapeutic approaches for the restoration of orofacial function.

Temporomandibular joint disorders (TMD) are common dysfunctions of the masticatory region and are often linked to dislocation or changes of the temporomandibular joint (TMJ) disc. Magnetic resonance imaging (MRI) is the gold standard for TMJ imaging but standard clinical sequences do not deliver a sufficient resolution and contrast for the creation of detailed meshes of the TMJ disc. Additionally, bony structures cannot be captured appropriately using standard MRI sequences due to their low signal intensity. The objective of this study was to enable researchers to create high resolution representations of all structures of the TMJ and consequently investigate morphological as well as positional changes of the masticatory system. To create meshes of the bony structures, a single computed tomography (CT) scan was acquired. In addition, a high-resolution MRI sequence was produced, which is used to collect the thickness and position change of the disc for various static postures using bite blocks. Changes in thickness of the TMJ disc as well as disc translation were measured. The newly developed workflow successfully allows researchers to create high resolution models of all structures of the TMJ for various static positions, enabling the investigation of TMJ disc translation and deformation. Discs were thinnest in the lateral part and moved mainly anteriorly and slightly medially. The procedure offers the most comprehensive picture of disc positioning and thickness changes reported to date. The presented data can be used for the development of a biomechanical computer model of TMJ anatomy and to investigate dynamic and static loads on the components of the system, which could be useful for the prediction of TMD onset.