Principal component analysis: a novel analysis to evaluate the characteristics of osseointegration of different implant surfaces.

Ryo Jimbo, Julia Fernandez-Rodriguez, Young-Taeg Sul, Carina B Johansson

Index: Implant Dent. 20(5) , 364-8, (2011)

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Abstract

To apply a new statistical method (principle component analysis; PCA) to evaluate osseointegration.Two different commercially available implants were selected for the study. Twenty implants, 10 of each type, were placed in the rabbit tibiae (n = 10). The fluorochromes (FLCs) alizarin complexone and calcein green were administered after 20 days and 4 days before sacrifice for labeling. On the day of implantation and retrieval (6 weeks), implant stability was measured with a resonance frequency analyzer (RFA). The retrieved samples were ground sectioned for histomorphometric and FLC quantification. The collected data were analyzed by a PCA software program (Qlucore Omics Explorer, Lund, Sweden) to explore and determine the correlation between different study variables and to analyze the differences between different implants.The RFA presented no significant differences at either time point. The bone-to-implant contact was significantly higher for the TiUnite (NobelBiocare, Gothenburg, Sweden); however, the bone area and FLC quantification showed higher values for the Osseotite (3i Implant Innovation, FL). Consistent with these results, the PCA indicated a strong correlation between TiUnite and high bone-to-implant contact values and between Osseotite and high bone area and FLC values. No correlation between RFA and the biological responses were found.The application of the PCA analysis may help interpret and correlate results obtained from numerous evaluations.