Abstract
The present study analyzed stress distributions in craniofacial structures around implant-supported maxillary prostheses. Using post-hemimaxillectomy computed tomography (CT) of a patient, the authors constructed a three-dimensional (3D) solid model using Digital Imaging and Communications in Medicine data (DICOM data) for maxillofacial and cranial bones. The effects of different prosthesis designs on stress distributions in craniofacial bones and osseous tissues around the implants were biomechanically investigated using 3D finite-element analysis. Maxillary prostheses were designed with 2 implants in the zygoma on the affected side and 2–3 implants in the maxillary alveolar bone on the unaffected side, without using a cantilever. Zygomatic implants provided suitable stress dispersal to the zygomatic and craniofacial bones on the affected side. This information is useful for designing maxillary prostheses.
After maxillectomy, the maxilla and the buttresses are lost, and the oral cavity communicates with the nasal cavity and a maxillary sinus . This operation greatly impairs articulation and mastication . Maxillary obturator prostheses have a long history of effectively resolving the functional, cosmetic and psychological problems associated with the defects caused by maxillectomy, but the mobility of maxillary obturator prostheses impairs function. Mobility of maxillary prostheses is affected by the size and character of the defect, the height and contours of the residual alveolar ridge and palatal shelf, the availability of undercuts, and most importantly, by the health and position of any remaining teeth . In cases that have required extensive resections, significant problems regarding the retention, support and stability of maxillary obturator prostheses are encountered after ablation of the retentive maxillary anatomy. In such cases, the main issues are the restoration of functional recovery, for example by adjusting the level of occlusion, and improving the quality of life, prognosis and success rates for implanting maxillary prostheses.
Zygomatic implants were originally designed for reconstruction of the atrophic, edentulous maxilla. They have also been used to support and aid the retention of maxillary prostheses after maxillectomy , which is otherwise difficult. Clinical application of zygomatic implants has been developed primarily for the treatment of the maxilla showing severe resorption. The extent of stresses such as increasing occlusal force is high, but dynamic techniques for examining stress due to supporting implants are not available.
Few biomechanical studies have examined these prostheses with implants. In the present study, the authors analyzed stress distributions in craniofacial structures around implant-supported maxillary prostheses.
Stress was analyzed using three-dimensional (3D) finite-element analysis distributions in craniofacial structures around implant-supported maxillary prostheses. Using post-hemimaxillectomy computed tomography (CT) of a patient, the authors constructed a 3D solid model using Digital Imaging and Communications in Medicine (DICOM) data for maxillofacial and cranial bones. They simulated the prostheses design with implants for this patient with a computer. The information acquired from this study will contribute to designing maxillary prostheses with implants, leading to higher success rate.
Materials and methods
Construction of craniofacial bone models
Using 3D finite-element analysis, biodynamics were examined for a maxillary prosthesis with 1 or 2 zygomatic implants after right hemimaxillectomy for malignant maxillary tumor and a left alveolar bone prosthesis with 1–3 implants. Typical occlusal loads were simulated, and stress distributions in the maxillary prosthesis model with zygomatic and normal implants and surrounding osseous structures were examined.
A 3D, finite-element, solid model of the human skull was constructed based on randomly selected clinical CT data from a 63-year-old Japanese man with edentulous maxilla. Data were obtained after right hemimaxillectomy for malignant maxillary tumor.
The craniofacial part of the skull was scanned in the transverse plane using a SOMATRON Plus 4 Volume Zoom scanner (Siemens AG, Erlangen, Germany), with 1.0 mm slice thickness and 1.0 mm scan increment, resulting in 180 slice images. Mimics 10.11 image-processing software (Materialise, Leuven, Belgium) was used to generate 3D external shapes of the craniofacial and alveolar bones. Output data were transferred to Solidworks 3D computer-aided design software (SolidWorks Corp., Concord, MA, USA) for conversion to a finite-element solid model ( Fig. 1 ).
Maxillary prosthesis models
Brånemark System ® standard implants (Norbel Biocare AB, Gotebörg, Sweden) with dimensions of 3.75 mm × 13.0 mm and 3.0 mm high multi-unit abutments were used. The superstructure was modeled as a symmetrically curved gold alloy bar with a section of 10.0 mm × 8.0 mm and constructed using Solidworks.
Models of maxillary prostheses with different numbers of implants were prepared for the right maxillary defect. On the affected side, 1 or 2 implants were placed in zygomatic bone on the affected side: Z-1 group, 1 implant (Z-1); and Z-2 group, 2 implants (medial implant, Z-M; distal implant, Z-D). The following three implants were placed in the left unaffected alveolar bone: L-1, in the maxillary lateral incisor; L-2, in the maxillary first premolar; and L-3, in the maxillary first molar. The maxillary prostheses with 2 zygomatic implants in the zygomatic bone on the affected side were compared with alveolar bone on the unaffected side using different numbers of implants. Type 1 used 3 implants (L-1, L-2 and L-3) in the left alveolar bone. Types 2–4 used two implants (Type 2: L-2 and L-3; Type 3: L-1 and L-3; Type 4: L-1 and L-2). Types 5–7 used 1 implant (Type 5: L-1; Type 6: L-2; Type 7: L-3) ( Fig. 2 ). Under the condition of tilted implant placement, zygomatic implants were tilted 90° relative to the plane of resection, and left implants were tilted 90° relative to the vertical plane. Maxillary prostheses with these designs were compared and analyzed.
Craniofacial and maxillary prosthesis models were craniofacial bone model (craniofacial model) and maxillary prosthesis models. These models were observed to be coincidentally related and were read into a finite-elemental program (COSMOS/Works; Structural Research & Analysis Corp., Los Angeles, CA, USA) for mesh generation. The number of triangles describing the external shapes needed to be drastically reduced ( Fig. 1 ). Mesh generation yielded a total of approximately 170,000 elements and 260,000 nodes. Average element size was 4.0 mm for the craniofacial model and 1.0 mm for the implant model. The mechanical properties of components of these models were based on the results of previous studies .
Loading
Loading involved the application of a simulated bite force as a distributed vertical load of 150 N to the occlusal surface at the zygomatic implant axis, and a lateral load of 50 N to the palatal surface of the superstructure . A distributed bite force of 300 N was applied at the insertion area of the masseter muscle on the zygomatic arch and the zygomatic process of the maxilla to simulate movement of the masseter muscle in occlusion, passing downwards and backwards . With regard to boundary conditions, a fixed bond (i.e. osseointegrated implants) was assumed between the bone and implants along the entire interface, meaning that under the load applied on the implants, relative motion between the bone and implant did not occur. For the top and back cutting plane, restraints were selected to simulate the presence of the rest of the skull. Both loading and boundary conditions of finite-element models are shown in Fig. 3 .
Comparative stress analysis was performed using the 3D finite-element method regarding von Mises stresses, defined by the following equation. The amounts and distributions of main stresses on maxillary prostheses with zygomatic implants in the craniofacial region were compared for different restorative situations:
The von Mises stress = 1 2 [ ( σ 1 − σ 2 ) 2 + ( σ 2 − σ 3 ) 2 + ( σ 3 − σ 1 ) 2 ]
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