Finite element analysis of stress distribution in zygomatic implant configurations with different hybrid prosthesis superstructure materials
摘要
This finite element study aimed to comparatively evaluate the biomechanical performance of two zygomatic implant configurations combined with two hybrid prosthesis superstructure materials under simulated occlusal loading in severely atrophic maxilla. A three-dimensional model of a severely atrophic maxilla was reconstructed from cone-beam computed tomography data. Two configurations were evaluated: two conventional implants combined with two zygomatic implants (2CI–2ZI) and a quad-zygoma configuration (4ZI). Polymethyl methacrylate (PMMA) and monolithic zirconia superstructures were modeled over a CAD-CAM milled titanium bar. Eight models were loaded vertically (150 N) and obliquely (150 N at 30°). Maximum von Mises and maximum principal stress values were assessed at implant components, the titanium framework, and the prosthetic superstructure. The 4ZI configuration demonstrated more homogeneous stress distribution than the 2CI–2ZI configuration. Implant and titanium bar stresses were higher in PMMA superstructure models, whereas superstructure stress was higher in zirconia models; PMMA models also showed greater deformation. Oblique loading produced higher stress values across most models. The quad-zygoma configuration may provide more favorable load distribution in severely atrophic maxillary rehabilitation. The choice of hybrid prosthesis superstructure material significantly influences stress transfer to implant components and the supporting framework and should be considered a critical biomechanical variable in treatment planning. Implant configuration and prosthetic superstructure material are factors that may influence stress distribution within implant components and the supporting framework in zygomatic implant-supported rehabilitation. While the clinical significance of these biomechanical differences requires further investigation, clinicians may consider these variables alongside patient-specific factors such as bone quality and loading conditions when planning treatment.