Publication Date: 2016.
Objectives: The goal of this study is to contribute to a better quantitative description of the early stages of osseointegration, by application of fractal, multifractal, and lacunarity analysis. Materials and methods: Fractal, multifractal, and lacunarity analysis are performed on scanning electron microscopy (SEM) images of titanium implants that were first subjected to different treatment combinations of i) sand blasting, ii) acid etching, and iii) exposition to calcium phosphate, and were then submersed in a simulated body fluid (SBF) for 30 days. All the three numerical techniques are applied to the implant SEM images before and after SBF immersion, in order to provide a comprehensive set of common quantitative descriptors. Results: It is found that implants subjected to different physicochemical treatments before submersion in SBF exhibit a rather similar level of complexity, while the great variety of crystal forms after SBF submersion reveals rather different quantitative measures (reflecting complexity), for different treatments. In particular, it is found that acid treatment, in most combinations with the other considered treatments, leads to a higher fractal dimension (more uniform distribution of crystals), lower lacunarity (lesser variation in gap sizes), and narrowing of the multifractal spectrum (smaller fluctuations on different scales). Conclusion: The current quantitative description has shown the capacity to capture the main features of complex images of implant surfaces, for several different treatments. Such quantitative description should provide a fundamental tool for future large scale systematic studies, considering the large variety of possible implant treatments and their combinations. Clinical relevance: Quantitative description of early stages of osseointegration on titanium implants with different treatments should help develop a better understanding of this phenomenon, in general, and provide basis for further systematic experimental studies. Clinical practice should benefit from such studies in the long term, by more ready access to implants of higher quality.
Author affiliation: de Souza Santos, Daniel. Universidade Federal Rural Pernambuco; Brasil
Author affiliation: Cavalcanti Bezerra dos Santos, Leonardo. Universidade Federal de Pernambuco; Brasil
Author affiliation: de Albuquerque Tavares Carvalho, Alessandra. Universidade Federal de Pernambuco; Brasil
Author affiliation: Carneiro Leão, Jair. Universidade Federal de Pernambuco; Brasil
Author affiliation: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Author affiliation: Stosic, Tatijana. Universidade Federal Rural Pernambuco; Brasil
Author affiliation: Stosic, Borko. Universidade Federal Rural Pernambuco; Brasil
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas