New Matching Formulae to Examine Precision Fit of Implant Framework

Objectives: The traditional centroid method of measuring implant framework fit consists of four problems: (1) the fit at the edge is unknown, (2) the surface tested often vertically penetrates the opposing surface, (3) the mean diameter of the implant abutment and its replica becomes less than the real diameter if the Cartesian coordinate system statistical analysis method is used, and (4) The fixed coordinate system, #1 component (0,0,0), #5(x,0,0),and #3(x,y,0), is used for all the best fit matching. Wang et al. in 2004 solved the first three problems, and the new mathematical formulae presenting here solved the forth problem to improve the accuracy of best-fit calculations over traditional Centroid measurement.

Methods: One of 5 components on a framework was chosen to be the coordinate system origin (0,0,0) for best fit matching. The newly developed formulae determine the centroid vertical gap between the abutment of the master cast and the corresponding surface of the test framework for each component. The 2nd component demonstrating the minimum vertical centroid gap among the rest replicas was specified. The test framework was rotated and the centroid vertical gap of the 2nd component was adjusted to zero (x,0,0). Accordingly the replica demonstrating the 3rd minimum vertical centroid gap was found and rotated as zero (x,y,0). In the present method each component was assigned systematically as the matching coordinate system origin (0,0,0) so that total 5 best-fit cases will be generated from one paired master/test framework with 5 abutments and their replicas. The most precise best-fit case is selected from these 5 best-fit cases of each paired data for further statistical analysis. Polar coordinate system statistical analysis is utilized in this study.

Results:

Framework with 5 implants	The coordinate system used in matching	Mean vertical gap in mm (n=5)
		Centroid	Edge
			Maximum	Minimum
Casted	Fixed	0.210	0.375	0.044
	Unfixed	0.101	0.163	0.040
Machined	Fixed	0.059	0.086	0.033
	Unfixed	0.057	0.081	0.032

Conclusions: The unfixed coordinate system for matching generates better best-fit results compared to match in the fixed coordinate system.