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Influence of osseointegration degree and pattern on resonance frequency in the assessment of dental implant stability using finite element analysis.

Bin Deng, Keson Beng Choon Tan, Gui Rong Liu, Yi Lu

Open publisher page 22 citations

Abstract

PURPOSE: Resonance frequency analysis (RFA) has been widely used to predict dental implant stability by assessing conditions surrounding the implant. The aim of this study was to investigate the influence of osseointegration degree and pattern on the resonance frequency of implant-bone structure by means of finite element analysis (FEA). MATERIALS AND METHODS: A basic FEA model was created to represent a titanium implant in a portion of the maxillary bone at the left first premolar region. This model was then used to compute the vibration behaviors for 5 osseointegration degrees and 8 osseointegration pattern models using modal and harmonic analysis. RESULTS: In the arbitrarily set osseointegration pattern models, a significant influence of osseointegration degree on the resonance frequency (P < .001) could be expressed as the linear function R2 = 0.99. No significant influence from the osseointegration pattern could be observed (P = .89). While the coronal-osseointegration model had a slightly higher resonance frequency than others and the apical-osseointegration model had the lowest, the difference between the highest and lowest value was within 5% (P = .51). In the randomly set osseointegration models, the osseointegration degree had a statistically significant influence on the resonance frequency (P < .001); the pattern of random osseointegration for a certain osseointegration degree had little influence. CONCLUSION: It seems that RFA can detect implant-stability changes related to the increase in osseointegration degree. However, careful consideration should be given to its use in predicting the stability in vivo of loss of osseointegration at the marginal bone.

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PURPOSE: Resonance frequency analysis (RFA) has been widely used to predict dental implant stability by assessing conditions surrounding the implant. The aim of this study was to investigate the influence of osseointegration degree and pattern on the resonance frequency of implant-bone structure by means of finite element analysis (FEA). MATERIALS AND METHODS: A basic FEA model was created to represent a titanium implant in a portion of the maxillary bone at the left first premolar region. This model was then used to compute the vibration behaviors for 5 osseointegration degrees and 8 osseointegration pattern models using modal and harmonic analysis. RESULTS: In the arbitrarily set osseointegration pattern models, a significant influence of osseointegration degree on the resonance frequency (P < .001) could be expressed as the linear function R2 = 0.99. No significant influence from the osseointegration pattern could be observed (P = .89). While the coronal-osseointegration model had a slightly higher resonance frequency than others and the apical-osseointegration model had the lowest, the difference between the highest and lowest value was within 5% (P = .51). In the randomly set osseointegration models, the osseointegration degree had a statistically significant influence on the resonance frequency (P < .001); the pattern of random osseointegration for a certain osseointegration degree had little influence. CONCLUSION: It seems that RFA can detect implant-stability changes related to the increase in osseointegration degree. However, careful consideration should be given to its use in predicting the stability in vivo of loss of osseointegration at the marginal bone.

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Available abstract

PURPOSE: Resonance frequency analysis (RFA) has been widely used to predict dental implant stability by assessing conditions surrounding the implant. The aim of this study was to investigate the influence of osseointegration degree and pattern on the resonance frequency of implant-bone structure by means of finite element analysis (FEA). MATERIALS AND METHODS: A basic FEA model was created to represent a titanium implant in a portion of the maxillary bone at the left first premolar region. This model was then used to compute the vibration behaviors for 5 osseointegration degrees and 8 osseointegration pattern models using modal and harmonic analysis. RESULTS: In the arbitrarily set osseointegration pattern models, a significant influence of osseointegration degree on the resonance frequency (P < .001) could be expressed as the linear function R2 = 0.99. No significant influence from the osseointegration pattern could be observed (P = .89). While the coronal-osseointegration model had a slightly higher resonance frequency than others and the apical-osseointegration model had the lowest, the difference between the highest and lowest value was within 5% (P = .51). In the randomly set osseointegration models, the osseointegration degree had a statistically significant influence on the resonance frequency (P < .001); the pattern of random osseointegration for a certain osseointegration degree had little influence. CONCLUSION: It seems that RFA can detect implant-stability changes related to the increase in osseointegration degree. However, careful consideration should be given to its use in predicting the stability in vivo of loss of osseointegration at the marginal bone.

Key concepts: Osseointegration, Resonance frequency analysis, Implant, Dental implant, Dentistry, Biomedical engineering, Medicine, Surgery

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Influence of osseointegration degree and pattern on resonance frequency in the assessment of dental implant stability using finite element analysis. — Research Paper | ScholarLens