Understanding the Stress Distribution on Anatomic Customized Root-Analog Dental Implant at Bone-Implant Interface for Different Bone Densities

Nimmawitt, Pawhat; Aliyu, Aliyu M.; Lohwongwatana, Boonrat; Arunjaroensuk, Sirida; Puncreobutr, Chedtha; Mattheos, Nikos; Pimkhaokham, Atiphan

doi:10.3390/ma15186379

Cited by 11 publications

(10 citation statements)

References 49 publications

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“…To assess the stress distribution of custom anatomical root implants at the bone implant interface under different bone conditions, Pawhat Nimmawitt et al modeled four types of jaw bone with reference to Lekholm and Zarb's bone classification method [ 9 ]. Alexander Tsouknidas et al developed an isotropic jaw model representing four types of jaws in an experiment to assess the effect of different bone conditions on peri-implant bone stress distribution, but accurate modeling of bone is a challenge due to its inherent inhomogeneity and anisotropic features [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional finite element analysis of stress distribution on short implants with different bone conditions and osseointegration rates

et al. 2023

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Objective This experiment aimed to investigate the effects of bone conditions and osseointegration rates on the stress distribution of short implants using finite element analysis and also to provide some reference for the application of short implants from a biomechanical prospect. Materials and methods Anisotropic jaw bone models with three bone conditions and 4.1 × 6 mm implant models were created, and four osseointegration rates were simulated. Stress and strain for the implants and jaws were calculated during vertical or oblique loading. Results The cortical bone area around the implant neck was most stressed. The maximum von Mises stress in cortical bone increased with bone deterioration and osseointegration rate, with maximum values of 144.32 MPa and 203.94 MPa for vertical and inclined loading, respectively. The osseointegration rate had the greatest effect on the maximum principal stress in cortical bone of type III bone, with its value increasing by 63.8% at a 100% osseointegration rate versus a 25% osseointegration rate. The maximum and minimum principal stresses under inclined load are 1.3 ~ 1.7 and 1.4 ~ 1.8 times, respectively, those under vertical load. The stress on the jaw bone did not exceed the threshold when the osseointegration rate was ≥ 50% for Type II and 100% for Type III. High strain zones are found in cancellous bone, and the maximum strain increases as the bone condition deteriorate and the rate of osseointegration decreases. Conclusions The maximum stress in the jaw bone increases as the bone condition deteriorates and the osseointegration rate increases. Increased osseointegration rate reduces cancellous bone strain and improves implant stability without exceeding the yield strength of the cortical bone. When the bone condition is good, and the osseointegration ratio is relatively high, 6 mm short implants can be used. In clinical practice, incline loading is an unfavorable loading condition, and axial loading should be used as much as possible.

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Section: Introductionmentioning

confidence: 99%

Three-dimensional finite element analysis of stress distribution on short implants with different bone conditions and osseointegration rates

et al. 2023

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“…This 3D render can be edited using a software called AMIRA. 5,6 It was highlighted that a direct relationship existed between the CT number and HU. 8 The HU (Hounsfield unit) is an indicative of the density of bones from a radiological standpoint.…”

Section: Materials and Methodologymentioning

confidence: 99%

“…In biomechanical terms, the stress transmitted to the bone through the contact zone is expected to have an impact on both the bone regrowth as well as long-term clinical success as a result of it. 5,6 Despite other external factors, the transfer of stresses at the interface is critical to the success or failure, with an equally substantial contribution of the loading, the implant and the bone quality as well. 6 When compared to better density bone, poor-quality bone exhibits excessive resorption and impedes the healing process.…”

Section: Introductionmentioning

confidence: 99%

Evaluate the effect of bone density variation on stress distribution at the bone–implant interface using numerical analysis

Hindurao,

Gujare,

Jadhav

et al. 2024

Proc Inst Mech Eng H

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The current study aims to comprehend how different bone densities affect stress distribution at the bone–implant interface. This will help understand the behaviour and help predict success rates of the implant planted in different bone densities. The process of implantation involves the removal of bone from a small portion of the jawbone to replace either a lost tooth or an infected one and an implant is inserted in the cavity made as a result. Now the extent of fixation due to osseointegration is largely dependent on the condition of the bone in terms of the density. Generally, the density of the bone is classified into four categories namely D1, D2, D3, and D4; with D1 being purely cortical and D4 having higher percentage of cancellous bordered by cortical bone. A bone model with a form closely resembling the actual bone was made using 3D CAD software and was meshed using Hyper Mesh. The model was subjected to an oblique load of 120 N at 70° to the vertical to replicate occlusal loading. A finite element static analysis was done using Abaqus software. The stress distribution contours at the bone-implant contact zone were studied closely to understand the changes as a result of the varying density. It was revealed that as the quantity of the cancellous bone increased from D1 to D4 the cortical peak stress levels dropped. The bone density and the corresponding change in the material characteristics was also responsible for the variation in the peak stress and displacement values.

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“…Therefore, many studies used FEA to reduce overload before implant placement. Most studies conduct stress analysis based on new implants [48,49], changes in implant materials [50][51][52], and various variables [53]. Although this can achieve better implants and placement plans, it does not help with real-time placement depending on the condition of the patient.…”

Section: Summary Remarks and Conclusionmentioning

confidence: 99%

Toward Digital Twin Development for Implant Placement Planning Using a Parametric Reduced-Order Model

Ahn,

Kim,

Baek

et al. 2024

Bioengineering

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Real-time stress distribution data for implants and cortical bones can aid in determining appropriate implant placement plans and improving the post-placement success rate. This study aims to achieve these goals via a parametric reduced-order model (ROM) method based on stress distribution data obtained using finite element analysis. For the first time, the finite element analysis cases for six design variables related to implant placement were determined simultaneously via the design of experiments and a sensitivity analysis. The differences between the minimum and maximum stresses obtained for the six design variables confirm that the order of their influence is: Young’s modulus of the cancellous bone > implant thickness > front–rear angle > left–right angle > implant length. Subsequently, a one-dimensional (1-D) CAE solver was created using the ROM with the highest coefficient of determination and prognosis accuracy. The proposed 1-D CAE solver was loaded into the Ondemand3D program and used to implement a digital twin that can aid with dentists’ decision making by combining various tooth image data to evaluate and visualize the adequacy of the placement plan in real time. Because the proposed ROM method does not rely entirely on the doctor’s judgment, it ensures objectivity.

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Understanding the Stress Distribution on Anatomic Customized Root-Analog Dental Implant at Bone-Implant Interface for Different Bone Densities

Cited by 11 publications

References 49 publications

Three-dimensional finite element analysis of stress distribution on short implants with different bone conditions and osseointegration rates

Three-dimensional finite element analysis of stress distribution on short implants with different bone conditions and osseointegration rates

Evaluate the effect of bone density variation on stress distribution at the bone–implant interface using numerical analysis

Toward Digital Twin Development for Implant Placement Planning Using a Parametric Reduced-Order Model

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