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NUMERICAL PREDICTION OF DENTAL IMPLANT STABILITY: IN VITRO VALIDATION
Short Talk ST-24
S342
Bone and Dental
NUMERICAL PREDICTION OF DENTAL IMPLANT STABILITY: IN VITRO VALIDATION Thibaut Bardyn (1), Philippe Gédet (1), Wock Hallermann (2), Philippe Büchler (1)
1. University of Bern, MEM Research Center, Switzerland; 2. University Hospital of Bern, Switzerland
Introduction Dental implantology has had a huge impact on modern dentistry. Among other factors, primary implant stability is a prerequisite for long-term success of this procedure [Gapski, 2003]. However, the existing methods of evaluation only provide a measure of primary implant stability after placement. Computer assisted planning has been proven to be a useful tool for the placement of osseointegrated implants [Fortin, 2006]. However, with the existing softwares, no quantitative information regarding implant’s mechanical stability is available. Adding finite element analysis to the planning can give this missing information to predict short- and long-term stability information before implant placement. Moreover, it can help the surgeon to choose implant position and size. The aim of the present work is to validate a method which allows for planning implant position and provides, in near real-time, an assessment of implant stability.
In order to validate the predicted primary stability, dental implants (Straumann AG, Switzerland) with different geometries were inserted in polyurethane foam bone blocks (Sawbones, USA) with homogeneous densities. These blocks were composed of two layers of different densities and thickness. Twelve combinations of blocks were tested. The removal torque was measured for each situation using a hydraulic testing machine (MTS). Then, the removal torque was calculated with the in-house software.
Results A significant correlation (R2=0.9816) was found between the experimental removal torque and the finite element simulation (see figure 2).
Methods
The planning process is iteratively improved
1. The surgeon uses the software to virtually plan the location of the implant on the CT scans. 2. Peri-implant bone density information is extracted from the CT scans. Mechanical properties are automatically assigned to an implant-specific FE mesh. Various load cases are applied to evaluate implant stability. implant axis
displacement
X
Optimal implant location. The surgeon can perform the surgery
3. Displacement, stress, strain and strain energy density resulting from this structural problem are calculated in near real-time with a custom finite element solver. The predicted implant stability is calculated from these data. 4. The results are displayed to the surgeons, who can update the implant position until optimal placement.
Figure 1: Overview of the method used for predicting implant dental primary stability
Journal of Biomechanics 41(S1)
Figure 2: Correlation between experiments and simulation of primary stability
Conclusions The good results obtained with implants inserted a controlled environment are a first step to the validation of the tool. Further tests on sheep bone are currently being performed to assess the concept in more realistic conditions. This method is the first of a new generation of “smart” planning software that will offer more complete preoperative information on the outcome of surgery. The advantage of such a procedure is that it can also be extended to other types of osseointegrated implants.
References Gapski et al, Clin Oral Impl Res, 14:515-527, 2003. Fortin et al, Int J Oral Maxillofac Implants, 21:298304, 2006
16th ESB Congress, Short Talks, Tuesday 8 July 2008
S342
Bone and Dental
NUMERICAL PREDICTION OF DENTAL IMPLANT STABILITY: IN VITRO VALIDATION Thibaut Bardyn (1), Philippe Gédet (1), Wock Hallermann (2), Philippe Büchler (1)
1. University of Bern, MEM Research Center, Switzerland; 2. University Hospital of Bern, Switzerland
Introduction Dental implantology has had a huge impact on modern dentistry. Among other factors, primary implant stability is a prerequisite for long-term success of this procedure [Gapski, 2003]. However, the existing methods of evaluation only provide a measure of primary implant stability after placement. Computer assisted planning has been proven to be a useful tool for the placement of osseointegrated implants [Fortin, 2006]. However, with the existing softwares, no quantitative information regarding implant’s mechanical stability is available. Adding finite element analysis to the planning can give this missing information to predict short- and long-term stability information before implant placement. Moreover, it can help the surgeon to choose implant position and size. The aim of the present work is to validate a method which allows for planning implant position and provides, in near real-time, an assessment of implant stability.
In order to validate the predicted primary stability, dental implants (Straumann AG, Switzerland) with different geometries were inserted in polyurethane foam bone blocks (Sawbones, USA) with homogeneous densities. These blocks were composed of two layers of different densities and thickness. Twelve combinations of blocks were tested. The removal torque was measured for each situation using a hydraulic testing machine (MTS). Then, the removal torque was calculated with the in-house software.
Results A significant correlation (R2=0.9816) was found between the experimental removal torque and the finite element simulation (see figure 2).
Methods
The planning process is iteratively improved
1. The surgeon uses the software to virtually plan the location of the implant on the CT scans. 2. Peri-implant bone density information is extracted from the CT scans. Mechanical properties are automatically assigned to an implant-specific FE mesh. Various load cases are applied to evaluate implant stability. implant axis
displacement
X
Optimal implant location. The surgeon can perform the surgery
3. Displacement, stress, strain and strain energy density resulting from this structural problem are calculated in near real-time with a custom finite element solver. The predicted implant stability is calculated from these data. 4. The results are displayed to the surgeons, who can update the implant position until optimal placement.
Figure 1: Overview of the method used for predicting implant dental primary stability
Journal of Biomechanics 41(S1)
Figure 2: Correlation between experiments and simulation of primary stability
Conclusions The good results obtained with implants inserted a controlled environment are a first step to the validation of the tool. Further tests on sheep bone are currently being performed to assess the concept in more realistic conditions. This method is the first of a new generation of “smart” planning software that will offer more complete preoperative information on the outcome of surgery. The advantage of such a procedure is that it can also be extended to other types of osseointegrated implants.
References Gapski et al, Clin Oral Impl Res, 14:515-527, 2003. Fortin et al, Int J Oral Maxillofac Implants, 21:298304, 2006
16th ESB Congress, Short Talks, Tuesday 8 July 2008