Abstract
Background
This study aimed to investigate the influence of different titanium mesh thicknesses (0.1 mm, 0.2 mm, and 0.3 mm) on mechanical durability and stress distribution in guided bone regeneration using finite element analysis (FEA).
Methods
Three-dimensional mandibular bone models were reconstructed from cone-beam computed tomography (CBCT) data of a patient with a posterior alveolar defect. Custom titanium meshes with varying thicknesses were designed and virtually applied to the defect area. All models were subjected to a vertical force of 30 N to simulate masticatory loading. FEA simulations were performed using ALTAIR Hypermesh and OptiStruct software to evaluate von Mises stress distribution across the mesh, graft, and bone.
Results
The 0.1 mm mesh exhibited the highest stress concentrations (981.569 MPa), indicating a high risk of plastic deformation and potential graft damage (35.287 MPa). The 0.2 mm mesh provided moderate protection with improved stress distribution (mesh: 452.218 MPa, graft: 11.589 MPa). The 0.3 mm mesh showed the best mechanical performance, with the lowest stress values on both the mesh (226.205 MPa) and the graft (7.785 MPa). Bone stress remained below critical thresholds in all models.
Conclusion
Mesh thickness significantly affects the mechanical behavior and stress shielding capacity of titanium meshes in GBR applications. A thickness of 0.3 mm offers the most reliable mechanical performance. However, 0.2 mm meshes may serve as a viable alternative in cases requiring greater flexibility or lower cost, with caution toward borderline graft stress.
Keywords: Titanium mesh, Finite element analysis, Bone grafting, Mesh thickness, Guided bone regeneration
Background
Titanium mesh is a widely used biomaterial in orthopedic and dental implant applications due to its excellent mechanical properties, low density, and high biocompatibility [1, 2]. Its structural integrity, combined with favorable biological performance, makes it an ideal candidate for use in guided bone regeneration (GBR) procedures, where maintaining space for new bone formation and protecting the grafted area are essential [2]. However, the mechanical performance of titanium mesh is closely influenced by its thickness and structural design, which in turn affects its interaction with surrounding tissues and the long-term success of regeneration.
Mesh thickness is a critical factor affecting both the strength of the mesh itself and the pattern of stress distribution on the underlying graft and bone. While increased thickness generally enhances mechanical stability, it may also lead to elevated stress concentrations on adjacent hard and soft tissues, potentially impairing osseointegration and soft tissue healing [3]. Conversely, excessively thin meshes may lack the structural resilience needed to withstand masticatory forces, leading to deformation, early exposure, or compromised regenerative outcomes [4].
Recent studies have emphasized that titanium mesh thickness impacts not only mechanical resistance but also biological outcomes, including soft tissue healing and graft stability [5]. Although thinner meshes may offer superior flexibility and better adaptation to soft tissues, their limited resistance to compressive and shear forces can undermine long-term stability. On the other hand, thicker meshes provide enhanced mechanical support but may pose risks such as soft tissue ischemia or dehiscence due to excessive rigidity [6–8]. Furthermore, microarchitectural features such as pore geometry, perforation patterns, and three-dimensional configurations also influence the mesh’s regenerative potential by affecting angiogenesis, osteoconduction, and tissue integration [9, 10].
Finite Element Analysis (FEA) has emerged as a powerful tool in bioengineering and implant research, enabling detailed simulation of mechanical behavior in complex anatomical environments [11]. Through computational modeling, FEA can predict stress distributions and deformation under physiological loads, offering valuable insights into the biomechanical efficacy and safety of various biomaterial configurations [12]. Importantly, FEA provides a non-invasive and cost-effective method for optimizing implant design before clinical application.
The aim of this study is to comprehensively evaluate the biomechanical effects of titanium meshes with different thicknesses (0.1 mm, 0.2 mm, and 0.3 mm) on stress distribution and mechanical integrity using finite element analysis. By simulating mechanical loading conditions and analyzing stress propagation through mesh, graft, and bone, this investigation seeks to identify the optimal balance between structural support and biological compatibility. The findings of this study are expected to contribute to the development of more efficient and patient-specific GBR strategies, guiding clinicians in selecting the most appropriate mesh design for long-term clinical success.
Methods
Patient data and ethical approval
This study utilized radiographic data derived from a partially edentulous patient presenting with a mandibular bone defect, who was referred to the Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Istanbul University, for implant rehabilitation. The patient was selected based on the presence of a localized alveolar defect suitable for three-dimensional modeling and virtual surgical planning.
Prior to data collection, ethical clearance was obtained from the Clinical Research Ethics Committee of Istanbul University, Faculty of Dentistry (Approval No: 2024/67), in accordance with the principles outlined in the Declaration of Helsinki. Written informed consent was also secured from the patient for the use of anonymized radiological records in academic research.
A high-resolution cone-beam computed tomography (CBCT) scan of the mandibular region was used to generate a three-dimensional anatomical model. This digital model served as the basis for subsequent finite element reconstruction and surgical simulation procedures.
Image processing and model construction
The cone-beam computed tomography (CBCT) data obtained from the patient, with a slice thickness of 0.398 mm, were imported into 3D Slicer software (version 5.2.2; Kitware, Inc., USA) for initial image processing and anatomical segmentation. To differentiate hard tissue structures from surrounding regions, segmentation was performed using Hounsfield Unit (HU) thresholding, with the range set between 426.50 and 3193.04, which is suitable for isolating mineralized tissues such as cortical bone and dental structures.
Following segmentation, irrelevant anatomical components and imaging artifacts were manually eliminated using the software’s ‘Erase’ and ‘Scissors’ tools to ensure data accuracy. The cleaned segmented volumes were then converted into three-dimensional (3D) surface meshes and exported in STL (stereolithography) file format for subsequent model refinement (Fig. 1).
Fig. 1.
Preparation of models from tomography data in 3D Slicer software
The exported STL models were imported into Rhinoceros 3D software (version 8; Robert McNeel & Associates, Seattle, WA, USA) for advanced geometric editing and anatomical reconstruction. Within this environment, a high-fidelity model of the mandible, including individual dental units, was constructed with precise spatial fidelity. Additionally, a 2-mm-thick virtual soft tissue layer was digitally modeled to represent the oral mucosa, following the contour of the outer mandibular surface. All anatomical components were carefully aligned and spatially registered within a unified 3D coordinate system, thereby creating a biologically realistic digital model suitable for finite element analysis or surgical simulation.
Custom titanium mesh design
Based on the digitally reconstructed mandibular bone model, custom titanium meshes and mini screws were virtually designed to accommodate the anatomical contours and planned augmentation in the edentulous region corresponding to teeth numbers 45 through 47. The design process was carried out using Rhinoceros 3D software, employing a stepwise workflow to ensure anatomical accuracy and reproducibility.
Initially, the desired augmentation volume was outlined using the “pointcurve” function to define the graft contours over the alveolar defect. This curve was then transformed into a continuous surface to serve as the scaffold base. Mesh geometries were generated on this surface using patterning algorithms and subsequently extruded to produce three different titanium mesh thicknesses: 0.1 mm, 0.2 mm, and 0.3 mm, allowing for comparative mechanical evaluation. Each configuration was optimized to maintain structural integrity while ensuring minimal invasiveness (Fig. 2).
Fig. 2.
Steps of designing Ti Mesh and bone graft on the defect area (1–4)
Mini screws were modeled as cylindrical geometries with a diameter of 1.7 mm, and lengths of 5 mm (buccal) and 7 mm (lingual/palatal) to reflect clinical anchorage conditions. To replicate the biological envelope, the oral mucosa was digitally constructed in two distinct layers, with the crestal 2-mm zone identified and assigned as keratinized mucosa. All virtual components—bone, graft, titanium mesh, screws, and mucosal tissues—were then aligned and assembled into a cohesive anatomical model for biomechanical analysis.
Finite element modeling
The complete geometric assembly was exported from Rhinoceros 3D software and imported into HyperMesh software (version 2024.1; Altair Engineering Inc., Troy, MI, USA) for finite element preprocessing. High-resolution triangular surface meshes with an average element size ranging from 0.1 mm to 0.25 mm were applied to accurately capture surface morphology. Internal volumes were subsequently meshed using tetrahedral solid elements, ensuring fidelity in stress loading and structural behavior across all components.
All simulations were conducted using the OptiStruct solver (ALTAIR Engineering Inc., USA). The computational analyses were executed on a high-performance workstation equipped with an 11th Generation Intel® Core™ i9-11900 processor (2.50 GHz) and 64 GB ECC (Error-Correcting Code) RAM, to ensure numerical stability and processing efficiency for complex mesh models.
Material properties
All modeled materials were assumed to be homogeneous, isotropic, and linearly elastic to enable standard comparative evaluation under static loading conditions. The specific mechanical properties -namely, Young’s modulus and Poisson’s ratio- assigned to each anatomical and prosthetic component are summarized in Table 1.
Table 1.
Mechanical properties of materials used in the FEA
| Material | Elastic Modulus (MPa) | Poisson’s Ratio (ν) |
|---|---|---|
| Bone | 13,700 | 0.3 |
| Graft | 1000 | 0.3 |
| Tooth | 20,000 | 0.3 |
| Titanium Alloy | 110,000 | 0.3 |
| Lining Mucosa | 10 | 0.3 |
| Keratinized Mucosa | 50 | 0.3 |
MPa Megapascal, ν Poisson’s ratio
Loading conditions and boundary constraints
To replicate the biomechanical environment encountered during routine functional activities—such as mastication, oral hygiene maneuvers, or unintended external pressure—a static vertical load of 30 N was applied to the soft tissue surface overlying the titanium mesh [13]. This loading scenario was selected to represent a non-physiological yet clinically relevant force magnitude acting on the augmented region.
The applied force was uniformly distributed across the 100 most exposed nodal points on the occlusal and buccal surfaces of the mucosal layer, specifically in the area corresponding to the grafted defect site. This approach was chosen to simulate dispersed mechanical stress rather than a point-load application, thereby enhancing the model’s clinical relevance and avoiding unrealistic stress concentration artifacts (Fig. 3).
Fig. 3.
Force (1) and boundary conditions (2) models
To ensure model stability and mimic anatomical fixation during mastication, boundary constraints were applied by fixing all degrees of freedom (translation and rotation in X, Y, and Z directions) at nodes located along the posterior and basal cortical surfaces of the mandible. These regions were considered biomechanically stable and least affected by local stress propagation, making them ideal as anchorage sites for boundary fixation (Fig. 3).
A total of three nonlinear static analyses were performed, each using identical loading vectors and boundary definitions, to evaluate the mechanical response of the titanium meshes with different thickness configurations (0.1 mm, 0.2 mm, and 0.3 mm) Table 2.
Table 2.
Element and node statistics for each model
| Model | Total Nodes | Total Elements |
|---|---|---|
| Model 1 | 709,908 | 2,657,333 |
| Model 2 | 734,766 | 2,768,943 |
| Model 3 | 815,709 | 3,120,368 |
Contact definitions and assembly conditions
Accurate representation of biomechanical interactions between the model components was achieved through the definition of appropriate contact interfaces within the finite element environment. These interfaces were assigned using the integrated tools of the simulation software to reflect realistic mechanical behavior under functional loading.
Frictional interactions were introduced at the interfaces between the titanium mesh and the overlying mucosa, as well as between the mesh and the underlying bone graft. A coefficient of friction (µ = 0.2) was applied based on values commonly reported for metal–tissue and metal–bone interfaces [13]. This configuration permitted controlled micromovements and shear stress loading, while minimizing surface slippage, thereby enhancing the physiological accuracy of the model.
A “freeze” contact condition (fully bonded contact to simulate rigid fixation) was applied between the titanium mesh, mini screws, and the mandibular cortical bone, simulating the rigid mechanical stability achieved through surgical fixation. This setting enforced full constraint of relative motion, thereby assuming that the connected components behave as a single deformable body under load, consistent with the clinical behavior of rigid osteosynthesis systems.
RESULTS
Finite element analysis demonstrated that titanium mesh thickness significantly affected the distribution and magnitude of stress on the mesh itself, the underlying bone graft, and the recipient bone. In the 0.1 mm mesh model, the maximum von Mises stress observed on the mesh was 981.569 MPa, indicating critical levels that exceed the elastic limit of titanium alloy and suggest a potential for plastic deformation [14]. The thin structure of the mesh failed to effectively dissipate occlusal forces, resulting in elevated stress values in the graft area (35.287 MPa), which could increase the risk of microfractures or material fatigue in the graft material. Additionally, the stress transferred to the bone remained low (9.711 MPa), within the acceptable elastic range of cortical bone (Table 3; Fig. 4).
Table 3.
Maximum von mises stress values for titanium mesh, graft, and bone
| Mesh Thickness (mm) | Max Stress - Mesh (MPa) | Max Stress - Graft (MPa) | Max Stress - Bone (MPa) |
|---|---|---|---|
| 0.1 | 981.569 | 35.287 | 9.711 |
| 0.2 | 452.218 | 11.589 | 4.923 |
| 0.3 | 226.205 | 7.785 | 3.089 |
Fig. 4.
Von Mises stress distrubution in the 0.1 mm mesh model
MPa: megapascal.
For the 0.2 mm mesh model, stress distribution was more balanced. The maximum stress on the mesh dropped significantly to 452.218 MPa, with corresponding graft stress decreasing to 11.589 MPa (Table 3; Fig. 5). This indicated improved load-bearing capacity and reduced risk of graft deformation, suggesting this thickness to be a safer alternative with acceptable mechanical performance.
Fig. 5.
Von Mises stress distrubution in the 0.2 mm mesh model
The 0.3 mm mesh model exhibited the lowest stress values across all regions. The mesh absorbed the majority of the load, with a peak stress of 226.205 MPa. Graft stress was minimized to 7.785 MPa, and bone stress further decreased to 3.089 MPa (Table 3; Fig. 6). This configuration offered the most favorable mechanical profile, minimizing risk of deformation or failure in both graft and bone tissue.
Fig. 6.
Von Mises stress distrubution in the 0.3 mm mesh model
Overall, the 0.3 mm titanium mesh demonstrated superior mechanical behavior, with optimal load absorption and minimal risk of damage to the graft and surrounding bone. While the 0.2 mm mesh also provided acceptable safety margins and may offer advantages in flexibility and cost, its use should be carefully considered in cases involving high functional load or compromised bone support. The 0.1 mm mesh, due to its insufficient structural stability and high stress transmission, is not recommended for clinical use under load-bearing conditions.
Discussion
This study provides a detailed finite element analysis (FEA) of three different titanium mesh thicknesses (0.1 mm, 0.2 mm, and 0.3 mm) used in guided bone regeneration (GBR), evaluating their biomechanical behaviors and their effects on stress transmission to graft and underlying bone tissues. As implant-related GBR procedures increasingly rely on titanium meshes for spatial maintenance and mechanical protection of grafts, determining the ideal mesh thickness is essential to balance rigidity, adaptability, and biological integration [15, 16].
The primary biomechanical role of titanium meshes in GBR is to maintain graft volume and shield it from compressive and shear forces during the early healing phase, a period critical for angiogenesis and osteoblast recruitment [17, 18]. Previous studies have demonstrated that mechanical stability is a prerequisite for successful bone regeneration, as micromotion or stress concentration may disrupt cellular adhesion and matrix deposition [19, 20]. Therefore, mesh characteristics must be tailored not only for structural integrity but also for the preservation of the biological environment.
Our results show that mesh thickness directly influences stress distribution within the system. The thinnest configuration (0.1 mm) demonstrated an excessive concentration of von Mises stress on the mesh (981.569 MPa), surpassing the yield strength of widely used titanium alloys such as Ti-6Al-4 V (typically ~ 880–950 MPa) [14]. This indicates a significant risk of plastic deformation under physiological loading. Moreover, the inadequate load-absorbing capacity of the thin mesh resulted in stress transfer to the underlying graft (35.287 MPa), which may promote microfractures, resorption, or failure of the graft material, particularly if particulate xenografts or allografts are used, which possess lower mechanical resilience than autogenous grafts [21].
In contrast, the intermediate thickness (0.2 mm) demonstrated improved biomechanical performance. The stress on the mesh dropped by more than 50% (452.218 MPa), and graft stress was reduced to 11.589 MPa. These values suggest that the 0.2 mm mesh functions effectively as a partial stress buffer, absorbing and redistributing forces while avoiding excessive rigidity. This finding aligns with studies by De Santis et al. (2013), who emphasized that moderately stiff barrier materials optimize graft protection without compromising soft tissue closure [22–24]. However, it is worth noting that even though the 0.2 mm mesh represents a reasonable compromise, stress values remain near the upper limit of tolerable thresholds for some graft materials, suggesting careful patient selection and flap design are necessary.
The 0.3 mm mesh demonstrated the most favorable biomechanical characteristics in our study. With von Mises stress values of 226.205 MPa on the mesh, 7.785 MPa on the graft, and 3.089 MPa on the bone, this configuration offered optimal mechanical shielding. These stress levels remain safely within the elastic range for titanium and graft materials, reducing the risk of structural compromise during the healing process. Furthermore, minimal stress was transmitted to the underlying bone, preserving its mechanical and biological integrity. Low bone stress is particularly relevant in elderly or medically compromised patients with reduced bone quality, in whom excessive loading may provoke bone remodeling, resorption, or necrosis [25].
Another key insight derived from this study is the shift in load transfer dynamics with increasing mesh thickness. As mesh thickness increases, a larger proportion of the applied load is absorbed by the mesh itself, significantly reducing the stress imposed on the graft and bone. This load-buffering effect confirms the mechanical rationale behind the use of titanium meshes in GBR. However, the benefits of increased thickness must be cautiously balanced against surgical and biological constraints. Thicker meshes, while mechanically advantageous, are less malleable and more challenging to adapt intraoperatively [26]. They may require preoperative CAD/CAM design or pre-bending with stereolithographic models to conform accurately to the defect morphology [27]. It should be also considered that stress distribution varies with bone density and implant design in stress shielding and so decreasing implant stiffness can reduce stress in surrounding bone, using porous implants in weaker bones can mitigate stress shielding [28, 29].
The incidence of mesh exposure, infection, and soft tissue complications in clinical contexts for each mesh thickness was not addressed in this study. However, clinical data shows that titanium meshes may have high risks of soft tissue dehiscence and exposure with the rates of 21.53% [30]. This emphasizes the importance of considering patient-specific factors and anatomical variations when choosing mesh thicknesses for clinical applications.
The impact of surgical factors, such as incorrect screw placement, absence of primary closure, or mesh incompatibility, was also not explicitly modeled in this study. These factors can significantly affect the biomechanical stability of the mesh and graft system. For example, improper screw placement may lead to inadequate fixation, and the lack of primary closure could increase the risk of soft tissue dehiscence, both of which can negatively influence the overall outcome of the procedure.
Moreover, excessive mesh rigidity can negatively impact soft tissue integration. In patients with thin or high-risk gingival phenotypes, a rigid mesh may lead to soft tissue dehiscence, mucosal ischemia, or early exposure, all of which can compromise graft stability and increase the risk of infection [7, 8]. Therefore, while the 0.3 mm mesh offers the best mechanical outcomes in a purely structural sense, its clinical use should be guided by patient-specific anatomical and soft tissue considerations. Surgeons should adopt tension-free closure techniques, adequate flap release, and, when necessary, soft tissue augmentation to mitigate these risks.
This study also underlines the importance of finite element modeling as a predictive tool in implant and graft-related biomaterial selection. By simulating mechanical responses under controlled parameters, FEA enables a non-invasive, cost-effective way to assess the functional behavior of complex systems [31]. Our use of high-resolution tetrahedral meshing and isotropic linear elastic material assumptions allowed for consistent comparisons across groups [13]. However, the model has inherent limitations. It assumes linear, homogenous material properties and does not account for biological processes such as inflammation, soft tissue adaptation, angiogenesis, or remodeling. Moreover, loading was limited to a static 30 N vertical force—simplifying the complex, multidirectional, and cyclic forces experienced in the oral cavity.
Future research should incorporate dynamic simulations, time-dependent material properties, and multiphysics modeling to simulate the biological and mechanical interplay in GBR more realistically. To extrapolate the conclusions from static loading conditions to real-world conditions, it should be incorporated cyclic masticatory forces that vary in orientation and magnitude. This will allow for a more accurate representation of functional stresses that occur during chewing, which are dynamic and involve more complex loading patterns than the static forces applied in this study. Additionally, in vivo validation through prospective clinical trials is necessary to correlate the FEA findings with actual clinical outcomes. Long-term data regarding mesh exposure rates, graft resorption, and implant survival across mesh thicknesses would further refine our understanding and guidelines.
Conclusion
Titanium mesh thickness plays a critical role in mechanical stability and stress distribution during guided bone regeneration. Among the tested models, the 0.3 mm mesh demonstrated superior mechanical performance, minimizing stress on both graft and bone. While 0.2 mm meshes may be a cost-effective alternative with acceptable performance, thinner designs (0.1 mm) pose a higher risk of deformation and graft overload. These findings highlight the importance of thickness optimization in mesh selection to ensure successful regenerative outcomes.
Acknowledgements
The authors have no acknowledgements to declare.
Authors’ contributions
B.G. conceptualized the study and M.A.E. designed the experiments. M.B.K., G.E.D. and G.G.U. analyzed the data and B.G. wrote the manuscript. A.B.C. coordinated the revisions. All six authors read and approved the final manuscript.
Funding
This research was not supported by any scientific council.
Data availability
All relevant data and materials are available upon reasonable request. Please contact the corresponding author for access to the datasets and additional information related to this study.
Declarations
Ethics approval and consent to participate
Ethical approval for this study was obtained from the Clinical Research Ethics Committee of Istanbul University, Faculty of Dentistry (Approval No: 2024/67), in accordance with the Declaration of Helsinki. Informed consent to participate was obtained from the participant in the study.
Consent for publication
Written informed consent for publication was obtained from the patient. All data presented are anonymized, and no identifiable personal information is included.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All relevant data and materials are available upon reasonable request. Please contact the corresponding author for access to the datasets and additional information related to this study.