Finite Element Analysis of Functionally Loaded Subperiosteal Implants Evaluated on a Realistic Model Reproducing Severe Atrophic Jaws

Gerardo Pellegrino, Maryia Karaban, Veronica Scalchi, Marco Urbani, Amerigo Giudice, Carlo Barausse, Pietro Felice.

Full text link: https://pubmed.ncbi.nlm.nih.gov/39846694/

Finite Element Analysis of Functionally Loaded Subperiosteal Implants Evaluated on a Realistic Model Reproducing Severe Atrophic Jaws

1. Scientific Reference

• Study title: Finite Element Analysis of Functionally Loaded Subperiosteal Implants Evaluated on a Realistic Model Reproducing Severe Atrophic Jaws
• Authors: Gerardo Pellegrino, Maryia Karaban, Veronica Scalchi, Marco Urbani, Amerigo Giudice, Carlo Barausse, Pietro Felice.
• Journal: Methods and Protocols
• Publication year: 2025.
• DOI: 10.3390/mps8010008.

2. Scientific Background

Rehabilitation of patients with severe jaw atrophy remains one of the greatest challenges in contemporary implant dentistry. Extensive bone resorption often limits the placement of conventional endosseous implants, making advanced reconstructive procedures necessary. While bone augmentation techniques can restore implant sites, they frequently require multiple surgical interventions, longer treatment times, increased morbidity, and higher overall costs.

Advances in digital workflows, CAD/CAM technologies, and additive manufacturing have renewed interest in patient-specific subperiosteal implants as an alternative treatment option for extreme anatomical situations. Unlike conventional implants, these custom-made titanium frameworks are designed to rest directly on the cortical bone and are stabilized with fixation screws. Despite their growing clinical use, evidence-based design criteria regarding implant geometry, fixation strategy, and biomechanical optimization remain insufficiently established.

This study addresses these uncertainties through finite element analysis (FEA), investigating how different design modifications influence stress distribution within both the implant and surrounding bone under simulated functional loading.

3. Study Objective

The primary objective of this study was to investigate the biomechanical behavior of patient-specific subperiosteal implants designed for the rehabilitation of severely atrophic maxillae and mandibles using finite element analysis (FEA). The authors aimed to determine how variations in implant design—including the number and position of cortical fixation screws, implant extension, and the presence or absence of connecting bars between hemi-implants—influence stress distribution within both the implant framework and the supporting bone.

A secondary objective was to identify design configurations capable of improving load transfer while minimizing stress concentrations in critical cortical bone regions exposed to functional occlusal forces.

4. Methodology

This investigation was conducted as a preclinical computational study using finite element analysis. No clinical patients were enrolled, and no clinical outcomes or follow-up data were reported. Instead, anatomically realistic digital models of a severely atrophic maxilla and mandible were reconstructed from DICOM radiographic datasets. Following segmentation and surface reconstruction, customized subperiosteal implant designs were created and progressively modified to evaluate their biomechanical performance.

The numerical models incorporated cortical bone, cancellous bone, titanium implants, fixation screws, and prosthetic components. Material properties were assigned using isotropic linear elastic assumptions based on published values, while contact interactions between implant components and bone were defined using either bonded or frictional interfaces according to the expected mechanical behavior. A refined tetrahedral mesh was generated to accurately represent regions of particular biomechanical interest.

Five different static loading configurations were simulated to reproduce various functional chewing conditions. Each model was subjected to a vertical occlusal load of 500 N, and a cortical bone stress threshold of 50 MPa was adopted as the reference limit for evaluating potentially unfavorable stress concentrations. Multiple implant configurations (V0 through V6 for the maxilla, followed by corresponding mandibular designs) were analyzed sequentially to assess the biomechanical effect of specific structural modifications.

5. Main Findings

The simulations demonstrated that implant biomechanics were strongly influenced by both implant configuration and loading conditions. For both maxillary and mandibular models, the highest stress concentrations occurred during unilateral anterior loading (Configuration 3), whereas forces distributed across broader occlusal areas generated considerably lower stress levels within both the implant framework and surrounding bone.

Successive design refinements produced measurable improvements in mechanical performance. Introducing additional posterior fixation screws (Model V1) redistributed loading away from the anterior fixation points and generated a more balanced stress pattern throughout the implant. An alternative posterior screw orientation toward the vestibular aspect (Model V2) produced a biomechanical response comparable to V1 without offering a substantial advantage. Relocating anterior fixation toward the frontal process (Model V4) proved more effective than simply adding anterior screws (Model V3), reducing stress concentrations around cortical fixation sites while maintaining acceptable stress levels over the crestal support.

Under the most demanding anterior loading scenario, tensile stresses adjacent to certain cortical fixation screws exceeded 50 MPa, indicating localized areas of increased biomechanical demand. Conversely, implant configurations capable of distributing functional loads over larger support areas reduced stress within both the implant and adjacent bone. Maximum stresses within the titanium framework remained below the material’s yield strength, with localized peaks approaching 500 MPa, suggesting an adequate mechanical safety margin under the simulated conditions.

An additional finding was that connecting bars joining the right and left hemi-implants had virtually no influence on overall stress distribution. The numerical models indicated that the prosthetic superstructure itself provided sufficient rigidity, leaving the connecting bars minimally loaded during function. Similar biomechanical behavior was observed in both the maxillary and mandibular simulations.

6. Clinical Analysis

Rather than evaluating clinical success, this study investigates the mechanical behavior of customized subperiosteal implants before they are used in patients. Its principal contribution lies in demonstrating how relatively small modifications in implant design can substantially alter stress transmission throughout the implant–bone complex. Such information is particularly valuable during the engineering and planning phases of patient-specific implant development.

One of the most relevant findings concerns the strategic placement of cortical fixation screws. The simulations indicate that optimizing screw location is more influential than simply increasing the number of fixation points. Additional posterior fixation improved load sharing and reduced stress concentration in anterior regions, while repositioning anterior screws toward more favorable anatomical locations further optimized mechanical performance. These observations suggest that biomechanical planning should focus on the quality and distribution of fixation rather than on maximizing the amount of hardware.

The study also highlights that unilateral anterior loading represents the most demanding functional condition for subperiosteal implants. This finding has practical implications for digital implant design, as anterior loading scenarios should be considered when optimizing implant geometry and fixation strategies. Designing implants capable of dissipating these localized forces may reduce the risk of excessive mechanical loading in cortical bone.

Another noteworthy observation is the minimal biomechanical contribution of connecting bars between right and left hemi-implants. According to the numerical models, the prosthetic restoration itself provides sufficient structural rigidity, while the connecting bars transmit little mechanical stress. Although this finding could eventually simplify certain implant designs, it should not be interpreted as clinical evidence supporting the elimination of connecting elements. The present investigation evaluates only theoretical mechanical behavior under simulated conditions.

It is equally important to recognize the limitations inherent to finite element analysis. The computational models cannot reproduce biological healing, bone remodeling, patient-specific variability, long-term functional adaptation, or prosthetic complications. Consequently, the favorable biomechanical behavior observed in the simulations cannot be directly translated into clinical performance or long-term implant survival.

Overall, this work illustrates how finite element analysis can serve as an effective design optimization tool for patient-specific subperiosteal implants. By identifying stress concentration patterns before manufacturing, computational modeling may contribute to improving implant geometry and fixation strategies. Nevertheless, prospective clinical investigations remain necessary to determine whether these biomechanical improvements ultimately translate into superior patient outcomes.

7. Clinical Applications

The findings of this study primarily apply to the digital design phase of customized subperiosteal implants intended for patients with severe maxillary or mandibular atrophy. The simulations suggest that optimizing implant geometry and cortical screw positioning may improve biomechanical load distribution before fabrication, potentially contributing to more mechanically balanced implant designs.

These results are particularly relevant for fully digital implant workflows integrating three-dimensional imaging, CAD/CAM planning, and additive manufacturing of patient-specific titanium frameworks. They may assist clinicians, engineers, and manufacturers involved in designing implants for cases where conventional endosseous implants or extensive bone augmentation procedures are not feasible because of insufficient residual bone volume.

From a research perspective, the study supports the use of finite element analysis as a valuable engineering tool during implant development. However, the numerical findings should not be interpreted as clinical recommendations, since no patient outcomes, biological responses, or long-term performance data were evaluated.

8. Level of Evidence, Limitations and Transparency

This publication represents a preclinical computational study based on finite element analysis. While this methodology provides detailed insight into implant biomechanics, it represents a lower level of clinical evidence than prospective clinical studies, randomized controlled trials, or systematic reviews.

The strength of the study lies in its use of anatomically realistic digital models reconstructed from radiographic data and in the systematic comparison of multiple implant configurations under standardized loading conditions. Nevertheless, the simulations rely on several assumptions regarding material properties, contact interfaces, and loading scenarios. Biological processes such as osseointegration, bone remodeling, patient-specific anatomical variability, and long-term fatigue behavior cannot be fully reproduced within the computational environment.

Accordingly, the principal limitation is the absence of clinical validation. No patients were treated, no implant survival rates were reported, and no biological or prosthetic complications were assessed. Therefore, the findings should be interpreted as biomechanical evidence supporting implant design optimization rather than as proof of clinical effectiveness.

Regarding transparency, several authors are affiliated with BTK Dental, a company involved in the development of customized medical devices. This affiliation is explicitly reported in the publication and should be acknowledged as a relevant contextual element. However, within the information provided, no specific conflict of interest statement indicating that these affiliations influenced the study findings is reported.

9. Key Study Highlights

• Study type: Preclinical finite element analysis (FEA).
• Level of evidence: Preclinical computational biomechanical study.
• Population/model: Anatomically realistic digital models of a severely atrophic maxilla and mandible.
• Number of patients: Not specified in the information provided.
• Number of implants: Multiple customized subperiosteal implant configurations (V0–V6 for the maxilla, with corresponding mandibular design variations).
• Follow-up duration: Not applicable.
• Primary outcome: Biomechanical stress distribution within customized subperiosteal implants and surrounding cortical bone under different loading conditions.
• Main finding: Implant geometry and cortical screw positioning substantially influenced stress distribution, while unilateral anterior loading generated the highest biomechanical stresses.
• Scientific conclusion: Finite element analysis appears to be a valuable design optimization tool for patient-specific subperiosteal implants intended for rehabilitation of severely atrophic jaws.
• Main limitations: Computational study only; no clinical validation, no patient outcomes, and results depend on the assumptions used in the numerical models.

10. Scientific Impact

This study makes a meaningful contribution to the growing body of research on patient-specific subperiosteal implants by providing a systematic biomechanical evaluation of multiple implant design strategies using anatomically realistic digital models. Rather than assessing clinical performance, the investigation focuses on the engineering principles that influence mechanical behavior before an implant is manufactured and placed in a patient.

The findings reinforce the concept that implant stability is not determined solely by material strength but also by the spatial distribution of cortical fixation and the way functional forces are transferred throughout the implant–bone–prosthesis complex. By demonstrating measurable differences between successive implant configurations, the study illustrates how computational modeling can guide evidence-based design decisions during the development of customized implant systems.

Another important contribution is the observation that not every structural modification leads to improved biomechanical performance. In particular, the simulations suggest that connecting bars between right and left hemi-implants contribute minimally to stress redistribution when the prosthetic superstructure already provides sufficient rigidity. Although this conclusion requires clinical validation, it offers an interesting perspective for future implant design optimization.

More broadly, the study supports the expanding role of digital implantology, where advanced imaging, CAD/CAM technologies, additive manufacturing, and numerical simulation are increasingly integrated into patient-specific treatment planning. The work also highlights the need for prospective clinical studies capable of determining whether the biomechanical advantages identified through finite element analysis ultimately translate into improved implant survival, prosthetic stability, and long-term patient outcomes.

11. Editorial Conclusion

This preclinical investigation demonstrates the value of finite element analysis as a design optimization tool for customized subperiosteal implants intended for the rehabilitation of severely atrophic jaws. The simulations indicate that careful optimization of cortical screw positioning and implant geometry can substantially improve biomechanical load distribution, whereas certain structural modifications provide little additional mechanical benefit.

Although these findings should not be interpreted as evidence of clinical superiority, they provide a scientifically sound framework for improving the engineering of patient-specific implant systems. Future clinical investigations will be essential to determine whether the biomechanical advantages observed in these simulations can be translated into improved long-term implant stability, reduced biological complications, and predictable clinical outcomes for patients requiring complex implant-supported rehabilitation.