Evaluation of prostheses retained zygomatic and dental implants in large defects in the maxilla due to tumors or major trauma by biomechanical 3- dimensional finite element analysis
Maxillary defects resulting from causes such as tumours and trauma are commonly encountered in clinical practice . After a maxillectomy, part of the maxilla is lost, creating a connection between the oral cavity, maxillary sinus, and nasal cavity . As a result, the deterioration in chewing and speech negatively impacts the quality of life of patients . Rehabilitation of atrophic maxillae with dental implants is challenging due to several limitations, including pneumatization of the maxillary sinus, severe alveolar bone resorption, and insufficient subnasal bone volume . Various techniques have been proposed for the treatment of maxillary atrophy, including reconstruction of the maxilla with the iliac crest, elevation of the maxillary sinus floor, bone grafts, and titanium mesh. Some of these treatment options necessitate multiple surgical interventions. Additionally, these procedures have varying success rates and often involve high surgical costs. The application of zygomatic implants is a less invasive method that offers more predictable results . Therefore, zygomatic implants, applied in various numbers and configurations, have been successfully used as a viable alternative to more complex surgical procedures in the rehabilitation of atrophic maxilla . Schmidt et al. , reported that the combination of zygomatic and standard endosseous implants can provide retention and support for maxillary obturator prostheses following extensive resection of the maxilla. As a result of the predictable implant support and retention provided, the planning of implant-supported obturator prostheses has become an effective treatment method . However, the design of the dental superstructure significantly affects the loading of dental implants and bone deformation. This deformation can lead to excessive stress accumulation in the bone surrounding the implants, resulting in bone resorption and potential implant failure . The transfer of load and distribution of stress in the implant-bone connection area are critical factors affecting the success rate of implants. Direct clinical evaluation is necessary to assess the biomechanical response of an implant to the surrounding bone. However, this is often impractical due to complex structures, lengthy operating times, and ethical concerns. Consequently, in vitro methods such as strain gauges, analytical techniques, experimental approaches, computational models, and finite element analysis (FEA) have been employed to evaluate the biomechanical behaviour of dental implants. Each of these methods has its advantages and limitations. However, FEA is indispensable for analysing situations involving numerous complex geometries and various implant configurations . FEA is an effective computational tool adapted from the engineering field for dental implant biomechanics, allowing for the evaluation of stress . FEA divides a complex body into smaller components that can be modelled separately using mathematical equations . FEA is widely used to assess the biomechanical performance of various dental implant designs and their effects on clinical factors related to implant success . With FEA, both the stress distribution on implants and abutments and the stress distribution in the bone supporting these implants can be evaluated . This study aimed to evaluate the amount and distribution of stress in implants and peri-implant bone in prosthetic models designed with different configurations of zygomatic and dental implants for Aramany Class I maxillary defects. Additionally, the study aimed to understand the prognosis of these treatment options using FEA.   FEA decomposes a model with continuous geometry into numerically simplified, smaller finite elements to address complex mechanical and physical problems in engineering applications . Apart from various technical fields, FEA is widely used in biomechanics  particularly in dental implantology and dental traumatology, as well as in general dentistry . In the dental context, FEA can be applied in biomechanical analysis, stress analysis, and personalized treatment planning, which enhances its significance in the field of dental implantology. In this study, the ANSYS Workbench software package (ANSYS 16.0, Swanson Analysis Systems Inc., Houston PA, USA) was utilized for numerical modelling and finite element analysis of the physical problem. To conduct a finite element analysis of an existing dental issue, an accurate numerical model must first be created. During this stage, the most appropriate geometry for the numerical model is developed, and the most suitable finite elements are selected to form the mesh structure. Choosing the right finite element geometry and size is crucial for the accuracy of the results. The mesh structure is constructed using the selected finite elements (geometry and mesh structure). The material properties for the created mesh structure are then defined (material properties). Finally, finite element analysis is performed based on the specified boundary conditions and loading scenarios (loads and boundary conditions). Geometry In this study, cone beam computed tomography (CBCT) images were used to create the geometric contours of the finite element (FE) model for the diagnosis and treatment planning of a middle-aged woman with maxillary edentulism. In this context, the institutional approvals from the Faculty Board of Recep Tayyip Erdoğan University and the Non-Invasive Ethics Committee were obtained first. CBCT images of materials were acquired using the NewTom VGI evo [Quantitative Radiology, Verona, Italy] with the following parameters: 125 μm voxel size, 110 Kvp, 4.06 mA, and a 6-second scan. CBCT images of a middle-aged woman with maxillary edentulism were randomly selected from the dentomaxillofacial radiology department archives and acquired using the NewTom VGI evo with the following parameters: 200 μm voxel size, 110 Kvp, 3 mA, and a 1.8-second scan. Data consisting of radiographic images saved as Digital Imaging and Communications in Medicine (DICOM) files were imported into Mimics Innovation Suite 24.0 (Materialise NV, Leuven, Belgium) for segmentation. The bone structure, soft tissues, and teeth of the maxilla were separated by the original images. At this stage, while creating the solid model of the maxilla, each detail was segmented and refined according to image intensity using Materialize 3-matic 16.0 (Materialise, Belgium, Leuven). The 3D model of the maxillary structure was segmented and cleaned to match the original. After making the necessary adjustments to the 3D model using SolidWorks (Solidworks 2018, Dassault Systemes Solidworks Corporation. Waltham MA, USA.), a complete 3D reconstruction of the maxillary structure was created and integrated into the ANSYS Workbench program for finite element analysis (Fig. ). In this study, a standard dental implant (Nobel Biocare AB) with a diameter of 4.3 mm and a length of 10 mm and a height of 3.5 mm multi-unit (0 0 ) abutments, and a zygomatic implant (NobelZygoma 45 0 TiUnit, Nobel Biocare AB, Gothenburg, Sweden) with a diameter of 4.1 mm and a length of 40 mm and a height of 3 mm multi-unit (0 0 ) abutments were used. Titanium screws produced as standard for the implant used as screws were used. After the implants were modeled, they were mounted in their planned locations on the modeled skull. It was also assumed that implants were fully osseointegrated (in full contact). Within the context of the study, modelling and analysis were conducted on three different scenarios for both the intact and defect regions of the maxilla. Zygomatic implant number 4 and standard dental implants numbered 2, 4, and 6 were projected into the maxilla in three different configurations (Fig. A, B, C). Finite element analyses were performed under various loading conditions for each design. In the first model, zygomatic implant number 4 was placed in the defect region of the maxilla, while standard dental implants numbered 2, 4, and 6 were positioned at appropriate angles in the non-defect region (Fig. A). In the second model, zygomatic implant number 4 was again placed in the defect area of the maxilla, and standard dental implants numbered 2 and 4 were positioned at appropriate angles in the non-defect area (Fig. B). Finally, in the third model, zygomatic implant number 4 was placed at appropriate angles in both the defect and non-defect areas of the maxilla (Fig. C). After the implants were placed in the prepared models as planned, the restorations were completed. In each model, frameworks consisting of both resin and Co-Cr materials were prepared. For Co-Cr framework; standard dental implant connected with a height of 3.5 mm multi-unit (0 0 ) abutments. Then, multi-unit and framework connection was provided with multi-unit abutment clinical screws. Zygomatic dental implant connected with and a height of 3 mm multi-unit (0 0 ) abutments. Then, multi-unit and framework connection was provided with multi-unit abutment clinical screws. For acrylic framework; standard and zygomatic dental implant connected with and a height of 3 mm locator (0 0 ) abutments. Then, locator and acrylic framework connection was provided with a male nylon cap and metal housing . Then, prosthetic models were created with maximum 2 mm thickness porcelain layer on a Co-Cr framework  and acrylic layer on an acrylic framework. Mesh structure The solid models obtained for the three scenarios were transferred to ANSYS Workbench software for finite element analysis, with meshing performed separately for each model. To achieve realistic results, careful attention was given to selecting the optimal size of the finite elements for the mesh structures and using the appropriate finite elements. Consequently, a convergence study was conducted on the element dimensions to increase the overall accuracy of the mesh structure, minimize the variations in the values ​​and determine the optimal mesh size. In all models, mesh sizes were progressively reduced from coarse to fine until the stress values converged. Additionally, mesh refinements were applied in contact regions to enhance accuracy. Each finite element in the mesh structure was characterized by a Solid 92 element with a tetrahedral configuration consisting of 8 nodes. The mesh structure was created by combining finite elements sized at 0.075 mm for the teeth, 1 mm for the maxilla structure, 0.25 mm for the standard dental implants, and 0.25 mm for the zygomatic implant. Each finite element used was designed to accommodate displacement and rotation along the x, y, and z axes. The mesh structure of each model comprised a total of 1,273,408 nodes and 834,067 finite elements (Fig. ). Finally, each mesh structure was modelled as isotropic, homogeneous, and linear elastic. Material properties The mechanical properties of the materials used for each maxillary model and implant system were determined by the literature. At this stage, Young’s modulus (E), Poisson’s ratio (ν), and material density values obtained from the literature for cancellous bone, compact bone, dental bone, titanium implants, titanium abutments, titanium abutment screws, and zygomatic implants were assigned to match the physical properties of each structure. All specified materials were modelled as isotropic, homogeneous, and linear elastic. The mechanical properties of all materials used in the study were taken from previous studies and are detailed in Table . Loads and boundary conditions Before proceeding to the FEA, the boundary conditions of the model were defined, and simulations were performed under different loading conditions. To simulate a realistic maxillary model, boundary conditions were assumed to be constant (zero displacement) at the junction of the maxilla (both the defect and non-defect regions) with the zygomatic bone. For the loading scenarios, a static force of 150 N (to simulate bite load) was first applied to the defect area, then to the non-defect area, and finally to both areas separately at an angle relative to the occlusal surfaces (vertical plane). Subsequently, a static force of 150 N perpendicular to the occlusal surfaces (again simulating bite load) was applied to the defect area, the non-defect area, and finally to both areas separately . Based on the previous study, the applied 150 N load was distributed to the premolar and molar teeth . This load was distributed to 30 points, each consisting of 5 N force. 5-point vertical loads were applied to the premolars and 10-point vertical loads were applied to the molars. The loads were distributed as 25 N to the premolars and 50 N to the molars. The force was distributed to the central fossa and the side of the palatal cusp (functional cusp) facing the central fossa (Fig. ). Finite element analyses were performed under these conditions and loadings, with maximum stress and deformation values for the maxillary structure and implants recorded. The results obtained were examined comparatively. The stress and deformation distribution of the maxillary structure following the analysis is shown in Fig. .   In this study, cone beam computed tomography (CBCT) images were used to create the geometric contours of the finite element (FE) model for the diagnosis and treatment planning of a middle-aged woman with maxillary edentulism. In this context, the institutional approvals from the Faculty Board of Recep Tayyip Erdoğan University and the Non-Invasive Ethics Committee were obtained first. CBCT images of materials were acquired using the NewTom VGI evo [Quantitative Radiology, Verona, Italy] with the following parameters: 125 μm voxel size, 110 Kvp, 4.06 mA, and a 6-second scan. CBCT images of a middle-aged woman with maxillary edentulism were randomly selected from the dentomaxillofacial radiology department archives and acquired using the NewTom VGI evo with the following parameters: 200 μm voxel size, 110 Kvp, 3 mA, and a 1.8-second scan. Data consisting of radiographic images saved as Digital Imaging and Communications in Medicine (DICOM) files were imported into Mimics Innovation Suite 24.0 (Materialise NV, Leuven, Belgium) for segmentation. The bone structure, soft tissues, and teeth of the maxilla were separated by the original images. At this stage, while creating the solid model of the maxilla, each detail was segmented and refined according to image intensity using Materialize 3-matic 16.0 (Materialise, Belgium, Leuven). The 3D model of the maxillary structure was segmented and cleaned to match the original. After making the necessary adjustments to the 3D model using SolidWorks (Solidworks 2018, Dassault Systemes Solidworks Corporation. Waltham MA, USA.), a complete 3D reconstruction of the maxillary structure was created and integrated into the ANSYS Workbench program for finite element analysis (Fig. ). In this study, a standard dental implant (Nobel Biocare AB) with a diameter of 4.3 mm and a length of 10 mm and a height of 3.5 mm multi-unit (0 0 ) abutments, and a zygomatic implant (NobelZygoma 45 0 TiUnit, Nobel Biocare AB, Gothenburg, Sweden) with a diameter of 4.1 mm and a length of 40 mm and a height of 3 mm multi-unit (0 0 ) abutments were used. Titanium screws produced as standard for the implant used as screws were used. After the implants were modeled, they were mounted in their planned locations on the modeled skull. It was also assumed that implants were fully osseointegrated (in full contact). Within the context of the study, modelling and analysis were conducted on three different scenarios for both the intact and defect regions of the maxilla. Zygomatic implant number 4 and standard dental implants numbered 2, 4, and 6 were projected into the maxilla in three different configurations (Fig. A, B, C). Finite element analyses were performed under various loading conditions for each design. In the first model, zygomatic implant number 4 was placed in the defect region of the maxilla, while standard dental implants numbered 2, 4, and 6 were positioned at appropriate angles in the non-defect region (Fig. A). In the second model, zygomatic implant number 4 was again placed in the defect area of the maxilla, and standard dental implants numbered 2 and 4 were positioned at appropriate angles in the non-defect area (Fig. B). Finally, in the third model, zygomatic implant number 4 was placed at appropriate angles in both the defect and non-defect areas of the maxilla (Fig. C). After the implants were placed in the prepared models as planned, the restorations were completed. In each model, frameworks consisting of both resin and Co-Cr materials were prepared. For Co-Cr framework; standard dental implant connected with a height of 3.5 mm multi-unit (0 0 ) abutments. Then, multi-unit and framework connection was provided with multi-unit abutment clinical screws. Zygomatic dental implant connected with and a height of 3 mm multi-unit (0 0 ) abutments. Then, multi-unit and framework connection was provided with multi-unit abutment clinical screws. For acrylic framework; standard and zygomatic dental implant connected with and a height of 3 mm locator (0 0 ) abutments. Then, locator and acrylic framework connection was provided with a male nylon cap and metal housing . Then, prosthetic models were created with maximum 2 mm thickness porcelain layer on a Co-Cr framework  and acrylic layer on an acrylic framework.   The solid models obtained for the three scenarios were transferred to ANSYS Workbench software for finite element analysis, with meshing performed separately for each model. To achieve realistic results, careful attention was given to selecting the optimal size of the finite elements for the mesh structures and using the appropriate finite elements. Consequently, a convergence study was conducted on the element dimensions to increase the overall accuracy of the mesh structure, minimize the variations in the values ​​and determine the optimal mesh size. In all models, mesh sizes were progressively reduced from coarse to fine until the stress values converged. Additionally, mesh refinements were applied in contact regions to enhance accuracy. Each finite element in the mesh structure was characterized by a Solid 92 element with a tetrahedral configuration consisting of 8 nodes. The mesh structure was created by combining finite elements sized at 0.075 mm for the teeth, 1 mm for the maxilla structure, 0.25 mm for the standard dental implants, and 0.25 mm for the zygomatic implant. Each finite element used was designed to accommodate displacement and rotation along the x, y, and z axes. The mesh structure of each model comprised a total of 1,273,408 nodes and 834,067 finite elements (Fig. ). Finally, each mesh structure was modelled as isotropic, homogeneous, and linear elastic.   The mechanical properties of the materials used for each maxillary model and implant system were determined by the literature. At this stage, Young’s modulus (E), Poisson’s ratio (ν), and material density values obtained from the literature for cancellous bone, compact bone, dental bone, titanium implants, titanium abutments, titanium abutment screws, and zygomatic implants were assigned to match the physical properties of each structure. All specified materials were modelled as isotropic, homogeneous, and linear elastic. The mechanical properties of all materials used in the study were taken from previous studies and are detailed in Table .   Before proceeding to the FEA, the boundary conditions of the model were defined, and simulations were performed under different loading conditions. To simulate a realistic maxillary model, boundary conditions were assumed to be constant (zero displacement) at the junction of the maxilla (both the defect and non-defect regions) with the zygomatic bone. For the loading scenarios, a static force of 150 N (to simulate bite load) was first applied to the defect area, then to the non-defect area, and finally to both areas separately at an angle relative to the occlusal surfaces (vertical plane). Subsequently, a static force of 150 N perpendicular to the occlusal surfaces (again simulating bite load) was applied to the defect area, the non-defect area, and finally to both areas separately . Based on the previous study, the applied 150 N load was distributed to the premolar and molar teeth . This load was distributed to 30 points, each consisting of 5 N force. 5-point vertical loads were applied to the premolars and 10-point vertical loads were applied to the molars. The loads were distributed as 25 N to the premolars and 50 N to the molars. The force was distributed to the central fossa and the side of the palatal cusp (functional cusp) facing the central fossa (Fig. ). Finite element analyses were performed under these conditions and loadings, with maximum stress and deformation values for the maxillary structure and implants recorded. The results obtained were examined comparatively. The stress and deformation distribution of the maxillary structure following the analysis is shown in Fig. .   In this study, the distribution and magnitude of stresses on the bone were examined by applying loads to zygomatic and standard implants. Stresses were calculated as the maximum values of principal stress, defined as the maximum or minimum normal forces occurring in a loaded model, and von Mises stress, which indicates whether the material will yield or fracture. Three-dimensional loading simulations were conducted using FEA to calculate these stresses. Understanding the stress magnitudes in the model and the regions where stresses are concentrated is significant during the design or decision-making phases. Based on the stress conditions, experts can make informed decisions regarding the materials to be used or the type of treatment, helping to prevent potential complications and improve patient outcomes. Different implant models and loading conditions were created to examine various scenarios. Each scenario was analyzed separately using acrylic layer on acrylic framework and porcelain layer on CoCr framework and the results were compared. Table provides details of the boundary conditions and loading conditions used in the analysis. The stress values obtained under the given model details and boundary conditions in Table are compared in Fig. for maximum principal stress and in Fig. for maximum von Mises stress. When examining Fig. for the implant models, the greatest maximum principal stress value under all boundary conditions was observed in Model 3, while the smallest value was found in Model 1 when both porcelain layer on CoCr framework and acrylic layer on acrylic framework were used as prosthetic materials. Although the stress values for Models 2 and 3 are close to each other across all boundary conditions, the stress value for Model 1 is significantly lower than those of the other two models. Regarding the boundary conditions, the highest maximum principal stress value was recorded under the HL-D&ND (horizontal loading on the defective and non-defective areas) loading condition, while the lowest maximum principal stress value was noted under the VL-ND (vertical loading on the non-defective area) loading condition across all models. Additionally, using porcelain layer on CoCr framework as a prosthetic material slightly decreased the stress values compared to using acrylic layer on acrylic framework. When examining Fig. , it can be observed that the maximum von Mises stress values obtained in the implant models using both porcelain layer on CoCr framework and acrylic layer on acrylic framework as prosthetic materials are close and, in some cases, nearly identical under the same boundary conditions. Unlike the maximum principal stress values, the maximum von Mises stress values did not exhibit significant differences under different boundary conditions, nor did they show substantial variations when the loading condition was altered. Furthermore, using acrylic layer on acrylic framework instead of porcelain layer on CoCr framework as the prosthetic material slightly increased the stress values in the models.   Excessive stress between the implant and bone is a significant factor contributing to bone loss around the implant and failures in osseointegration. Therefore, estimating the scenarios in which stress levels will peak is crucial for the success of implant-supported prostheses . In the present study, prosthetic models containing various configurations of zygomatic and dental implants were designed to address unilateral maxillary defects using the FEA method. It was found that increasing the number of dental implants applied to the non-defective area resulted in lower maximum principal stress values; however, there was no significant difference between the models regarding von Mises stress values. FEA was employed in the current study because it enables the estimation of stress values between the implant and the bone, while also facilitating the modelling of various prosthetic designs. The accuracy of the tests conducted in FEA studies is influenced by the properties of the materials, interface definitions, geometries, and applied forces . Consequently, the modelling in this study was based on data obtained from a real CT scan. Additionally, to better reflect real-world conditions, the obturator prosthesis was modelled, and loads were applied directly to it. The maximum principal stress and von Mises stress values are the most commonly used metrics for evaluating stress distribution on bone. The maximum principal stress indicates the stress concentrated in a specific region, while the von Mises stress value allows for the assessment of material yielding and failure . Therefore, both stress values were evaluated in the current study. The number of implants used in implant-supported prostheses and their placement significantly affect the stress values between the implant and the bone, as well as the overall success of the prosthesis . In the present study, three different models were created, revealing that the highest maximum principal stress value was observed in Model 3 (with one zygomatic implant placed in both the defected and non-defective areas), while the lowest value was found in Model 1 (with one zygomatic implant in the defected area and three dental implants in the non-defective area). The stress values in Models 2 (one zygomatic implant in the defected area and two dental implants in the non-defective area) and 3 were close to each other, whereas the stress value in Model 1 was considerably lower than in the other two models. In contrast, Akay et al.  planned three different implant-supported locator attachment prostheses for Aramany Class 4 maxillary defects and found that, unlike this study, the use of a zygomatic implant in the non-defective area reduced the maximum principal stress values. They also reported that using a zygomatic implant in a non-defective area was more advantageous than employing one or two dental implants with locator attachments . Wang et al.  investigated the retention provided by clasps and the resistance of abutments to excessive torque forces by creating models of unilateral maxillary defects using a conventional prosthesis, one zygomatic implant, and two zygomatic implants. The results of their study indicated that the stress values in the models with zygomatic implants were significantly lower than those in the model with a conventional prosthesis, with the lowest stress value observed in the model featuring two zygomatic implants. They concluded that zygomatic implant-supported prostheses are effective for the restoration of unilateral maxillary defects . Freedman et al.  recorded von Mises stress values in their study investigating the effect of alveolar bone support on the stress distribution of zygomatic implants placed in the extra-sinus position. As a result of this study, they found that less stress occurred in the model without a maxillary defect and that the support provided by the alveolar bone was beneficial for zygomatic implants . In the present study, the maximum von Mises stress values obtained in different implant models created under the same boundary conditions were found to be close to each other and, in some cases, almost equal. Korkmaz et al.  reported in their study that they created four different bar-retained prosthesis models supported by zygomatic and dental implants in the presence of a unilateral maxillary defect. They found that the use of zygomatic implants in the non-defective area reduced the von Mises stress value and that increasing the number of dental implants in the non-defective area did not reduce the highest stress value. In the present study, the von Mises stress values in models prepared using zygomatic implants or different numbers of dental implants in the non-defective area were found to be close to each other, even when the direction of the applied force and the area where it was applied was changed. The maximum bite force in patients with osseointegrated implants has been reported as 144.4 N . Therefore, in many studies, a force of 150 N has been applied to simulate the actual maximum bite force . In the present study, a force of 150 N was applied to the models. Additionally, the direction of the applied force is also important. Therefore, in this study, both vertical and lateral forces were applied to reflect chewing forces more realistically. In the present study, when evaluated according to the forces applied to the models, the highest maximum principal stress value was observed when horizontal force was applied simultaneously to the defected and non-defective areas, while the lowest value was observed when vertical force was applied to the non-defective area. Additionally, when the loading conditions were changed in the models, the maximum von Mises stress values obtained did not show significant differences, similar to the maximum principal stress values. Unlike this study, Korkmaz et al.  found the lowest von Mises stress value in models where they placed zygomatic and dental implants in the non-defective area when vertical force was applied to that area. They also found similar values in models where vertical force was applied separately to the defected and non-defective areas in the model where they applied only dental implants to the non-defective area, while they found higher von Mises stress values when they applied vertical force simultaneously to both the defected and non-defective areas . Akay et al.  found the highest stress value when force was applied to both sides in the model where one dental implant was placed in the non-defective area, while the lowest stress value was found in the model where one zygomatic implant was placed in the non-defective area. They reported that the distribution of stresses on the prostheses could be more rational with the help of zygomatic implants, which could distribute the stresses to each part of the maxilla . Varghese et al.  applied two types of treatment methods in a severely atrophic edentulous maxilla model. In the first model, one conventional and one zygomatic implant was placed in each quadrant, while in the second model, two zygomatic implants were placed bilaterally in each quadrant. A vertical force of 150 N, a lateral force of 50 N, and an occlusal force of 300 N were applied to the models. When vertical force was applied, the stress was distributed more widely in the model with conventional implants. However, when lateral force was applied, significantly higher stress was determined in the model with conventional implants compared to the other model. When vertical and lateral forces were applied simultaneously, the highest von Mises stress value was found in the model with four zygomatic implants. In the present study, the highest maximum principal stress value in the model with zygomatic implants placed in the non-defective area was found when horizontal force was applied simultaneously to both the defected and non-defective areas. Although the von Mises value was not significantly different among the models, it was slightly higher in this model. After implant placement, different prosthetic restorations, such as all-acrylic and metal framework-supported options, can be applied for temporary or final prostheses . The framework materials may be an important factor in stress transmission to the implant-bone connection area . Additionally, using all-acrylic prosthetic restorations has shown the most prosthodontic problems, such as fractures in the prosthesis . In a previous study, the stress distribution of frameworks in different prosthodontic concepts (All-on-4 and All-on-6) was compared using a 3D FEA study. They concluded that stiffer framework materials (CoCr and Zr) decreased stress levels in different areas and exhibited the most suitable biomechanical behaviour. Furthermore, they noted that the titanium framework performed poorly in the All-on-4 prosthesis concept . In the present study, the use of a prosthesis made using an acrylic layer on acrylic framework instead of a prosthesis made using porcelain layer on Co-Cr framework as a material slightly increased both the maximum principal stress values and the von Mises stress values. In comparison with the current study, Arınç et al.  found similar results. They used FEA to evaluate the effects of prosthesis material on the stress levels in cortical bone, trabecular bone, and implants. Their findings showed that zirconia-reinforced polymethyl methacrylate (ZRPMMA; Poisson’s ratio (v): 0.3, Elastic modulus: 3.05 GPa) increased the maximum principal stress and von Mises stress values in implants and bone tissue more than Co-Cr and Zr while having the lowest von Mises stress value in the framework. When evaluated in terms of the materials used, although the Poisson ratios are the same in this study and Arınç et al. , there is a slight difference in the elastic moduli. There are some limitations to this study. First, muscle forces were not applied while vertical and horizontal forces were applied. The force during chewing could have been reflected more realistically by incorporating muscle forces. Second, all implants were assumed to be 100% osseointegrated. Another limitation is that all materials were assumed to be homogeneous, linearly elastic, and isotropic. While these results may help understand real-life conditions, more studies are needed.   Within the limits of this study, when both porcelain layer on Co-Cr framework and acrylic layer on acrylic framework were used, the highest maximum principal stress value was observed in the model with a single zygomatic implant applied to the non-defective area, while the lowest value was observed in the model with three dental implants placed in the non-defective area. In all models, the highest maximum principal stress value was obtained when horizontal force was applied simultaneously to both the defected and non-defective areas, while the lowest value was found when vertical force was applied to the non-defective area. When both porcelain layer on Co-Cr framework and acrylic layer on acrylic framework were used, the von Mises stress values were found to be close to each other across the models and under different loading conditions.   