Setting properties of bone substitutes are improved using an injectable system. The injectable bone graft substitutes can be molded to the shape of the bone cavity and set in situ when injected. Such system is useful for surgical operation. The powder part of the injectable bone cement is included of β-tricalcium phosphate, calcium carbonate, and dicalcium phosphate and the liquid part contains poly ethylene glycol solution with different concentrations. In this way, prediction of the mechanical properties, setting times, and injectability helps to optimize the calcium phosphate bone cement properties. The objective of this study is development of three different adaptive neurofuzzy inference systems (ANFISs) for estimation of compression strength, setting time, and injectability using the data generated based on experimental observations. The input parameters of models are polyethylene glycol percent and liquid/powder ratio. Comparison of the predicted values and measured data indicates that the ANFIS model has an acceptable performance to the estimation of calcium phosphate bone cement properties. 1. Introduction Bioactive calcium phosphates such as hydroxyapatite (HA) Ca10(PO4)6(OH)2, tricalcium phosphate (TCP) Ca3(PO4)2, tetracalcium phosphate (Ca4P2O9), and dicalcum phosphate (DCP) CaHPO4 have been widely applied for hard tissue substitute materials, due to their good biocompatibility and bioactivity [1–4]. Many studies have evidenced the excellent biocompatibility of calcium phosphates (CaPs) and their favorable interaction with hard tissue [5, 6]. The shapes of CaPs for the practical uses are classified into the dense and porous CaP blocks [7, 8], the powders and granules , the CaP coating [10, 11], and the CaP cement [12, 13]. The hardened forms of CaPs have a major disadvantage. One of the shortcomings is the difficulty of fitting into the defects. The particulate form of CaP can easily fill the defects; however, it migrates or disperses into surrounding tissue [14, 15]. One of the major improvements in CaPs in recent years is the development of an injectable system. The injectable bone graft substitutes can mold to the shape of the bone cavity and set in situ when injected. Such systems should shorten the surgical operation time, reduce the damaging effects of large muscle retraction, decrease the size of the scars and diminish postoperative pain. It also allows the patient to achieve rapid recovery in a cost-effective manner [15, 16]. Calcium phosphate cements (CaPCs) were the first injectable bone filling developed for bone substitute
S. M. Rabiee, F. Moztarzadeh, H. Salimi-Kenari, M. Solati-Hashjin, and S. M. J. Mortazavi, “Study of biodegradable ceramic bone graft substitute,” Advances in Applied Ceramics, vol. 107, no. 4, pp. 199–202, 2008.
M. R. Sarkar, N. Wachter, P. Patka, and L. Kinzl, “First histological observations on the incorporation of a novel calcium phosphate bone substitute material in human cancellous bone,” Journal of Biomedical Materials Research, vol. 58, pp. 329–334, 2001.
S. M. Rabiee, S. M. J. Mortazavi, F. Moztarzadeh et al., “Mechanical behavior of a new biphasic calcium phosphate bone graft,” Biotechnology and Bioprocess Engineering, vol. 13, no. 2, pp. 204–209, 2008.
H. Y. Song, A. H. M. E. Rahman, and B. T. Lee, “Fabrication of calcium phosphate-calcium sulfate injectable bone substitute using chitosan and citric acid,” Journal of Materials Science, vol. 20, no. 4, pp. 935–941, 2009.
P. Weiss, P. Layrolle, L. P. Clergeau et al., “The safety and efficacy of an injectable bone substitute in dental sockets demonstrated in a human clinical trial,” Biomaterials, vol. 28, no. 22, pp. 3295–3305, 2007.
F. Drissens, M. Bolton, O. Bermudez, J. Planell, M. Ginebra, and E. Fernandez, “Effective formulatiom for the preparation of calcium phosphate hone cements,” Journal of Materials Science, vol. 5, no. 3, pp. 164–170, 1994.
F. J. Guild and W. Bonfield, “Predictive modelling of the mechanical properties and failure processes in hydroxyapatite-polyethylene (HapexTM) composite,” Journal of Materials Science, vol. 9, no. 9, pp. 497–502, 1998.
L. Cao, C. Zhang, and J. Huang, “Simulation of the ultrasonic precipitation process of nano-hydroxyapatite by an artificial neural network,” Journal Wuhan University of Technology, vol. 20, pp. 135–137, 2005.
H. Baseri, S. M. Rabiee, F. Moztarzadeh, and M. Solati-Hashjin, “Mechanical strength and setting times estimation of hydroxyapatite cement by using neural network,” Materials and Design, vol. 31, no. 5, pp. 2585–2591, 2010.