A pre-clinical model for the assessment of the osseointegration of dental implants

The replacement of missing teeth with dental implants is considered the gold standard of dental treatment1. Several new materials have been approved by the Food and Drug Administration (FDA) as potential implant materials. However, the effectiveness of these implant materials has not been proven clinically, particularly as dental implants. Various approaches have been developed to assess the osseointegration of dental implants in animal models2,3,4. Satisfactory results in preclinical research are essential prior to the translation into clinical application. Thus, the challenge to find a viable novel approach to assess the osseointegration of new dental implants remains open. There is a need for a model where the new implant and the gold standard implant could be inserted and tested using a split-mouth design which allows the random allocation of the experimental and control material within the oral cavity5. This will offer several advantages which include the marked reduction of the environmental variabilities to draw a robust conclusion6. In this study, we describe the first rabbit model that utilised a split-mouth design to study osseointegration in the oral cavity. Methods and Results: The study was carried out on adult New Zealand white rabbits, each received two implants; an experimental on one side, and a control on the opposite side. The implants were 8mm long and 2mm wide and were inserted in the extraction sockets of the secondary incisors of the anterior part of the maxilla (Figure 1). Results: All rabbits tolerated the surgical procedures and recovered without complications. Discussion and conclusions: The described model is safe, reproducible, standardised, requires minimal surgical skills and can be achieved using basic surgical instruments. The design lends itself for the evaluation of new dental implants including compromised conditions such as osteoporosis, poorly controlled diabetes and other immunocompromised states.

Author(s): Noura Alotaibi, Kurrt Naudi & Ashraf Ayoub

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