Investigation of Test Foods With Different Hardness and Size on Lower Jaw Movements and Occlusal Morphology Which Designed With Chewing Registrations of Different Test Foods

A fundamental objective in prosthodontic rehabilitation is the accurate replication of the patient's native occlusal architecture. Since the early 20th century, dentistry has endeavored to simulate the functional dynamics of the temporomandibular joint (TMJ) and mandibular motion through the use of mechanical articulators-metallic devices engineered to replicate mandibular kinematics. Over time, these articulators have evolved from basic models to more sophisticated, patient-specific systems. Initially, semi-adjustable articulators emerged, followed by the development of fully adjustable variants intended to more closely approximate individual anatomical parameters. Despite their improved accuracy, these devices are not without limitations.

While fully adjustable articulators represent the most anatomically faithful mechanical approximation of mandibular function, they remain inherently limited in precision and adaptability. The calibration of these devices and the accurate documentation of mandibular movements have been subjects of long-standing investigation within both clinical and academic domains of dentistry. In response to the intrinsic shortcomings of mechanical systems-such as susceptibility to material deformation and challenges in capturing dynamic motion-digital motion capture technologies began to emerge in 1989. This transition marked a significant shift toward enhancing the fidelity of mandibular movement analysis.

By 2002, advancements in digital dentistry enabled the integration of virtual articulators within computer-aided design environments, utilizing digitally captured mandibular movement data. This innovation substantially addressed the limitations associated with traditional mechanical articulators, including structural deformation, inaccuracies during physical registration, degradation of plaster or recording media, and logistical inefficiencies in transferring physical components between clinical and laboratory settings. Furthermore, digital systems introduced the critical advantage of data preservation and reproducibility-parameters difficult to achieve with analog models.

Despite ongoing enhancements, mechanical articulators remain incapable of fully replicating the complex anatomical and neuromuscular intricacies of the temporomandibular joint and its associated musculature. Initial efforts to digitally capture mandibular motion involved rudimentary electronic methodologies, which were subsequently refined through the application of ultrasonic and optoelectronic tracking technologies. These innovations significantly improved the spatial resolution and reliability of movement data, enabling more sophisticated integration with virtual modeling systems.

Contemporary techniques now permit the acquisition of mandibular motion data through three-dimensional video-based motion capture systems. When these dynamic recordings are overlaid onto digitized jaw models, a new paradigm in prosthetic design is achieved-allowing for the fabrication of dental restorations without reliance on either virtual or physical articulators. This method not only enhances anatomical precision but also minimizes procedural constraints associated with traditional systems.

These advancements stem from an ongoing pursuit to capture mandibular movements with greater anatomical accuracy and functional adaptability. The inherent complexity of mandibular kinematics-modulated by factors such as food size, texture, and initial occlusal positioning, as well as psychosocial influences during mastication-has historically challenged the capacity of both clinicians and devices to simulate real-world chewing behavior. Digital methodologies offer a more nuanced and individualized representation of these dynamic patterns.

As a result, clinicians are increasingly capable of designing restorations that optimize occlusal morphology, thereby supporting maximal masticatory efficiency in prosthetic and restorative procedures. Technological advancements have expanded the scope of mandibular motion analysis beyond conventional border movements to include real-time recordings captured during functional activities such as chewing. This progression offers a more accurate representation of intraoral dynamics under natural physiological conditions.

The existing body of literature predominantly focuses on the evaluation of masticatory parameters during test food consumption, including electromyographic activity of masticatory muscles, incisal separation distances, lateral excursion amplitudes, and the overall range of chewing cycles. These studies have collectively established that mastication is highly sensitive to the physical properties of food, particularly in relation to its texture, hardness, and size.

It has been well-documented that the nature of food significantly influences mandibular kinematics, with textural variations playing a pivotal role in altering chewing patterns. Numerous studies have investigated how differences in food hardness and dimensional properties affect masticatory behavior, shedding light on the adaptive responses of the jaw during functional loading.

Findings from research examining the influence of food size on mandibular motion generally indicate a positive correlation between food volume and chewing cycle duration. As food size increases, both the intensity of masticatory muscle activation and the amplitude and velocity of mandibular movement tend to rise correspondingly-suggesting a coordinated neuromuscular adaptation to mechanical demands.

With respect to food hardness, there is broad agreement that greater hardness elicits elevated masticatory muscle activity. However, the impact of hardness on other kinematic parameters-such as cycle duration, movement amplitude, and speed-remains inconclusive, reflecting interindividual variability and methodological differences across studies.

Furthermore, the current literature lacks clinical investigations directly comparing the occlusal morphology of prosthetic restorations derived from dynamic chewing records with those fabricated through conventional mechanical or virtual articulator-based methods, including those relying solely on border movement data. This absence underscores a significant knowledge gap regarding the potential functional advantages of mastication-based modeling over traditional techniques.

To address this deficiency, the present study will utilize optoelectronic motion capture systems to record mandibular movements within the Department of Prosthodontics. The study is grounded in the following hypotheses:

Null Hypothesis (H₀):

Variations in the hardness and consistency of test foods do not induce statistically significant angular deviations in mandibular movement patterns.

Alternative Hypotheses:

H₁: Prosthetic restorations designed using functional chewing records do not exhibit differences in occlusal morphology compared to those created via conventional or virtual articulators.

H₂: Patient-specific anatomical parameters-such as condylar path inclination and the Bennett angle-remain consistent across chewing recordings conducted with various test foods.

A statistical power analysis was conducted using G*Power version 3.1.9.7 (Franz Faul, Universität Kiel, Germany), referencing the methodological parameters established in Muric's 2018 study titled "Comparing the Precision of Reproducibility of Computer-Aided Occlusal Design to Conventional Methods." An effect size of 0.25 was applied, with a Type I error rate (α) of 0.20 and a statistical power (1-β) of 80%, resulting in a calculated minimum sample size of 20 participants. To ensure sufficient representation and allow for potential attrition, the final sample size was determined to be 24 individuals. Group comparisons will be analyzed using the Kruskal-Wallis test, while the Mann-Whitney U test will be applied for post hoc pairwise comparisons.

Participants will be recruited from among volunteer students enrolled at the Faculty of Dentistry, Istanbul University. Eligible subjects who meet the inclusion criteria will be identified and registered through the Prosthodontics Clinic. Appointment scheduling will be coordinated jointly with each participant, and subsequent communication will be maintained via telephone. Given the requirement for multiple sessions per participant, ease of accessibility is a key consideration in subject selection.

Since the experimental protocol necessitates the accurate performance of mandibular movements-including laterotrusion, retrusion, and protrusion-participants familiar with these movements are preferred. Accordingly, dental students from Istanbul University, who are both knowledgeable in these functional motions and readily accessible for repeated sessions, have been selected as the study population.

To minimize confounding variables arising from individual anatomical or functional variability, only systemically and dentally healthy individuals will be included. The inclusion criteria are as follows: absence of temporomandibular joint (TMJ) disorders or masticatory muscle dysfunction; no history of orthodontic treatment; intact permanent dentition with Angle Class I molar occlusion (excluding third molars); absence of dental implants, supernumerary teeth, or extensive prosthetic restorations; and no reported orofacial pain or muscle sensitivity. Additionally, participants must not exhibit any allergies or sensitivities to the test foods, and individuals unfamiliar with the selected food items will be excluded to avoid variability due to novelty effects.

The precise execution of mandibular movements during data acquisition is essential, as these recordings directly influence the accuracy and validity of experimental outcomes. In alignment with precedent set by similar research, dental students are often selected as participants due to their familiarity with standard mandibular movement patterns and their ability to follow clinical instructions with consistency. Moreover, their typical age range (18-25 years) aligns well with the study's inclusion criteria, which specify the presence of fully erupted dentition, Angle Class I occlusion, absence of extensive restorations, and no prior prosthetic or orthodontic intervention.

Each participant was assigned a unique identification number ranging from 1 to 24, which was used consistently throughout the study for confidentiality and data tracking purposes. Prior to participation, all subjects were thoroughly informed about the study's objectives, procedures, and potential risks. Informed consent was obtained in writing, confirming their voluntary agreement to participate. Clinical examination of all subjects included the administration of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) developed by Schiffman et al., to ensure the absence of TMJ-related pathology.

Initially, digital impressions of each participant's maxillary and mandibular arches, along with occlusal bite registrations, will be obtained using the Alliedstar intraoral scanner. The acquired datasets will be exported in Standard Tessellation Language (STL) format, enabling the creation of precise digital models for subsequent analysis and design procedures.

Subsequently, mandibular border movements will be documented using the JMA Optic optoelectronic motion capture system (Zebris GmbH, Isny, Germany). The apparatus comprises a head-mounted sensor array and a bite fork affixed to the vestibular surfaces of the mandibular teeth using autopolymerizing acrylic resin (Temdent Temporary Crown and Bridge Acrylic, Schütz Dental GmbH, Rosbach, Germany). This fixation ensures stable signal transmission without impeding mandibular closure. The bite fork is adjusted for proper leveling and retention before being secured in place.

Following acquisition of the facebow registration, the "Border Movement" module within the WinJaw 10.06 software (Zebris GmbH, Isny, Germany) will be activated on a Windows-based workstation. Subject-specific information will be entered into the system, after which the recording of mandibular border movements will commence. Participants will be instructed to perform three repetitions of each predefined mandibular movement-protrusion, retrusion, right laterotrusion, and left laterotrusion-in accordance with the manufacturer's guidelines.

Upon completion of the border movement recordings, participants will be asked to sequentially masticate five standardized test foods exhibiting varying levels of hardness and consistency. Each chewing session will be recorded using the same JMA Optic device under the "Chewing" module of the WinJaw software. These recordings will capture functional mandibular kinematics during real-time mastication for each food item, facilitating a direct comparison of motion dynamics across different material properties.

The test foods selected for this study encompass a spectrum of textural and hardness profiles:

1. Soft cheese (Sütaş Dairy Products, Istanbul, Turkey), similar texture to Gouda;
2. Raw carrots (hard texture);
3. Boiled carrots (20 minutes of boiling in boiling water, moderately soft);
4. Crispy bread (UNO Kruton, Istanbul, Turkey);
5. Pre-polymerized silicone impression material, used as a substitute for peanuts due to allergy concerns, as approved by the ethics committee. (extremely hard texture, pre-polymerized according to manufacturer's manual)

Each sample will be standardized to dimensions of 10 mm × 10 mm × 10 mm to ensure uniformity in mastication parameters.

Preparation and portioning of all test foods will be conducted under controlled conditions in the Department of Prosthodontics' designated laboratory kitchen. To maintain consistency, stainless steel molds in the form of rectangular prisms (10 × 10 × 10 mm) will be fabricated and used to shape each food sample to identical size specifications. This standardization is critical to eliminating volumetric variability during mastication analysis.

For the chewing motion analysis, the JMA Optic system will be configured via the "Chewing" module in the WinJaw software. As with prior recordings, the sensor fork will be secured to the vestibular surfaces of the mandibular dentition using acrylic resin. Participants will be instructed to chew each food sample for a standardized duration of 20 seconds. The kinematic data from each session will be recorded independently, thereby generating five distinct datasets-corresponding to the five different test foods-that will form Groups 3 through 7 in the final analysis.

Upon completion of all motion and chewing recordings, the digital maxillary and mandibular models of each participant will be imported into the Exocad 3.1 Plovdiv software suite (Exocad GmbH, Darmstadt, Germany). Utilizing the "Wax-up" module, the occlusal and incisal surfaces of the mandibular dentition will be uniformly reduced by approximately 2 millimeters to simulate tooth preparation and establish a baseline for prosthetic occlusal morphology design. This digital modification facilitates the subsequent restorative modeling phase.

Subsequent to model preparation, study cohorts will be established based on the type of mandibular movement data integrated into the design process:

Group 1: Digital models coupled with closure registration data will be mounted on a semi-adjustable virtual articulator (Artex CR, Aman Girrbach, Koblach, Austria) within the design software. Prosthetic restorations will be fabricated using this conventional virtual articulation method.

Group 2: The digital jaw models will be incorporated alongside the optoelectronically recorded border movement trajectories. This dataset will guide the design of prosthetic restorations that account for patient-specific mandibular border kinematics.

Groups 3 to 7: The digital models will be integrated with chewing movement datasets obtained from the five distinct test foods independently. Each chewing dataset will be employed to inform the occlusal morphology design, resulting in five separate restoration designs reflecting functional adaptations to varied masticatory conditions.

The finalized prosthetic occlusal designs will be exported to Geomagic Control X software (3D Systems, Rock Hill, SC, USA) for comprehensive three-dimensional superimposition analysis. This process will quantify linear and angular deviations among the various restoration groups as well as discrepancies relative to the baseline intraoral scans. The software will facilitate precise measurement of spatial differences to assess the fidelity and variability induced by differing mandibular motion inputs.

Furthermore, patient-specific anatomical parameters-such as condylar path inclinations during protrusive movement and Bennett angle metrics-extracted from device-generated reports will be systematically compared across chewing and border movement datasets to evaluate consistency and accuracy.

All statistical analyses will be performed utilizing SPSS version 28.1 (IBM Corp., Armonk, NY, USA). Prior to inferential testing, data distributions will be examined for normality employing the Kolmogorov-Smirnov test. Continuous variables will be summarized as means with standard deviations, whereas categorical variables will be presented as frequencies and percentages.

To assess the agreement between measurement methods, the mean measurement errors for each reference distance will be computed. These will subsequently be evaluated using Bland-Altman plots, appropriate for multiple observations per subject, to visualize and quantify bias and limits of agreement.

For parametric data conforming to normal distribution, group comparisons involving more than two cohorts will be conducted via one-way Analysis of Variance (ANOVA), followed by Tukey's Honestly Significant Difference (HSD) post hoc tests for pairwise group analyses.

Conversely, non-parametric data failing to meet normality assumptions will be compared using the Kruskal-Wallis test for multi-group comparisons. Where significant differences arise, Mann-Whitney U tests will be employed for post hoc pairwise evaluations. To account for multiple testing and control type I error rates, Bonferroni correction will be applied to all post hoc analyses.

A significance threshold will be set at p < 0.05 for all statistical tests.