Effect of Implant Diameter and Length on Stress Distribution for Titanium and Zirconia Implants by Using Finite Element Analysis (FEA)

Yeşildal, Ruhi; Karabudak, Filiz; Bayındır, Funda; Zamanlou, Hamid; Yıldırım, Melike Pınar; Sağsöz, Nurdan Polat; Şen, Sadri

doi:10.4236/oalib.1101211

Cited by 9 publications

(9 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In accordance with results obtained by previous studies,[2514] this study confirms that an increase in implant diameter and length reduces the stress magnitudes within cortical bone. The results of this study confirm the conclusion of various studies[251415] that implant diameter is an effective design parameter than implant length. In this study, Von Mises stress distributions at the implant–bone interface was localized in the cortical bone around the implant neck in all the models similar to findings of studies done previously.…”

Section: Discussionsupporting

confidence: 90%

Impact of implant diameter and length on stress distribution in osseointegrated implants: A 3D FEA study

Eazhil¹,

Swaminathan²,

Gunaseelan³

et al. 2016

J Int Soc Prevent Communit Dent

View full text Add to dashboard Cite

Aims and Objectives:Dimension of dental implant is an important parameter which has a considerable impact on the biomechanical load transfer characters and its prognosis. Excessive stress in the bone–implant interface may result in the failure of the implant. The aim of this study was to evaluate the impact of implant diameter and length on neighboring tissues around the implant. The results of the study will help in developing a scientific methodology to select appropriate implant diameter and length.Materials and Methods:In this study, tapered implants of different diameter and length were numerically analyzed using bone–implant models developed from computed tomography generated images of mandible with osseointegrated implants. The impact of various diameters on stress distribution was examined using implants with a length of 13 mm and diameters of 3.5 mm, 4.3 mm and 5.0 mm. Implants with a diameter of 4.3 mm and lengths of 10 mm, 13 mm, 16 mm was developed to examine the impact of various implant length. All materials were assumed to be linearly elastic and isotropic. Masticatory load was applied in a natural direction, oblique to the occlusal plane. The Statistical Package for the Social Sciences software package was used for statistical analysis.Results:Maximum von Mises stresses were located around the implant neck. It was demonstrated that there was statistically significant decrease in von Mises stress as the implant diameter increased.Conclusion:Within the limitations of this study there was statistically significant decrease in von Mises stress as the implant diameter increased.

show abstract

Section: Discussionsupporting

confidence: 90%

Impact of implant diameter and length on stress distribution in osseointegrated implants: A 3D FEA study

Eazhil¹,

Swaminathan²,

Gunaseelan³

et al. 2016

J Int Soc Prevent Communit Dent

View full text Add to dashboard Cite

show abstract

“…[ 13 ] Yeşildal et al suggested increase implant diameter over length for success. [ 14 ] Abraham et al found lower compressive and tensile stresses in the peri-implant bone in the RP model compared to the NP model. [ 15 ] Topkaya et al concluded that implant length and diameter are important in its success.…”

Section: Discussionmentioning

confidence: 99%

Factors affecting the survival rate of dental implants: A retrospective study

Raikar

Talukdar

Kumari

et al. 2017

J Int Soc Prevent Communit Dent

129

View full text Add to dashboard Cite

Aims and Objectives:Dental implants have emerged as new treatment modality for the majority of patients and are expected to play a significant role in oral rehabilitation in the future. The present study was conducted to assess various factors affecting the survival rate of dental implants.Materials and Methods:The present retrospective study was conducted in the Department of Prosthodontics. In this study, 5200 patients with dental implants which were placed during June 2008–April 2015 were included. Exclusion criteria were patients with hormonal imbalance, patients with chronic infectious disease, patients receiving immunosuppressive therapy, pregnant women, drug and alcohol addicts, and patients with severe periodontal diseases. Parameters such as name, age, gender, length of implant, diameter of implant, location of implant, and bone quality were recorded. Data were tabulated and statistically evaluated with IBM SPSS Statistics for Windows, Version 20.0., IBM Corp., Armonk, NY, USA.Results:Out of 5200 patients, 2800 were males and 2400 females. Maximum implants failures (55) were seen in age group above 60 years of age (males – 550, females –700). Age group <40 years (males – 750, females – 550) showed 20 failed implants. Age group 41–60 years (males – 1500, females – 1150) showed 45 failed implants. The difference was nonsignificant (P = 0.21). Maximum implant failure was seen in implants with length >11.5 mm (40/700) followed by implants with <10 mm (20/1650) and 10–11.5 mm (60/2850). The difference was significant (P < 0.05). Maximum implants failure (30/1000) was seen in implants with diameter <3.75 mm followed by implants with diameter >4.5 mm (16/1600) and implants with diameter 3.75–4.5 mm (50/2600). The Chi-square test showed significant results (P < 0.05). Mandibular posterior showed 3.3% implants failure, maxillary posterior revealed 2.2%, maxillary anterior showed 2.1%, and mandibular anterior showed 1% failure rate; this difference was significant (P < 0.05). Type I bone showed 0.3% implant failure, Type II showed 1.95%, Type III showed 3%, and Type IV revealed 0.8% failure rate; this difference was significant (P < 0.05).Conclusion:Age, length of implant, diameter of implant, bone quality, and region of implant are factors determining the survival rate of implants. We found that implant above 11.5 mm length, and with diameter <3.75 mm, placed in the mandibular posterior region, in Type III bone showed maximum failures.

show abstract

“…The structure parameters can be set as any value. However, the materials of dental implant can only be selected from several Ti alloys, so the material parameters of dental implant are limited [26][27][28][29].…”

Section: Problem Descriptionmentioning

confidence: 99%

High-Low Level Support Vector Regression Prediction Approach (HL-SVR) for Data Modeling with Input Parameters of Unequal Sample Sizes

Shi

Guo

et al. 2021

Int. J. Comput. Methods

View full text Add to dashboard Cite

Support vector regression (SVR) has been widely used to reduce the high computational cost of computer simulation. SVR assumes the input parameters have equal sample sizes, but unequal sample sizes are often encountered in engineering practices. To solve this issue, a new prediction approach based on SVR, namely as high-low level SVR approach (HL-SVR) is proposed for data modeling of input parameters of unequal sample sizes in this paper. The proposed approach consists of low-level SVR models for the input parameters of larger sample sizes and high-level SVR model for the input parameters of smaller sample sizes. For each training point of the input parameters of smaller sample sizes, one low-level SVR model is built based on its corresponding input parameters of larger sample sizes and their responses of interest. The high-level SVR model is built based on the obtained responses from the low-level SVR models and the input parameters of smaller sample sizes. A number of numerical examples are used to validate the performance of HL-SVR. The experimental results indicate that HL-SVR can produce more accurate prediction results than SVR. The proposed approach is applied to the stress analysis of dental implant, in which the structural parameters have massive samples but the material of implant can only be selected from Ti and its alloys. The obtained prediction results of the HL-SVR approach are much better than SVR. The proposed approach can be used for the design, optimization, and analysis of engineering systems with input parameters of unequal sample sizes.

show abstract

Effect of Implant Diameter and Length on Stress Distribution for Titanium and Zirconia Implants by Using Finite Element Analysis (FEA)

Cited by 9 publications

References 15 publications

Impact of implant diameter and length on stress distribution in osseointegrated implants: A 3D FEA study

Impact of implant diameter and length on stress distribution in osseointegrated implants: A 3D FEA study

Factors affecting the survival rate of dental implants: A retrospective study

High-Low Level Support Vector Regression Prediction Approach (HL-SVR) for Data Modeling with Input Parameters of Unequal Sample Sizes

Contact Info

Product

Resources

About