Identification of a surface texture parameter panel characterizing surface micromorphologies of differently processed oral implant surfaces.

Abstract

Objectives: Inconsistent characterization of oral implant microtopography makes it difficult to compare and evaluate available data on microtopography and the biological response to topographical characteristics. The aim of this investigation was therefore to identify a surface texture parameter panel that enables a discriminative characterization of differently processed oral implant surfaces.

Materials and methods: Surface micromorphologies of titanium- and ceramic-based biomaterials processed by machining or by machining and subsequent post-processing, including blasting, etching, anodization or porous sintering, were analyzed by scanning electron microscopy and white light interferometry. It was then analyzed which of the parameters S_a, S_q, S_z, S_sk, S_ku, S_tr, S_al, S_pd, S_pc, S_dq and S_dr best characterized morphological surface features and hence should be reported as minimum parameter panel for implant surface characterization.

Results: SEM demonstrated that each surface processing resulted in a specific and biomaterial-dependent micromorphology. The data revealed that the micromorphology of machined surfaces was best characterized by S_a, S_dr, S_tr and S_sk, and that for post-processed surfaces S_pd and S_pc were additionally required. Based on these data, S_a, S_dr, S_tr, S_sk, S_pd and S_pc were identified as minimum parameter panel for discriminative description of the investigated implant microtopographies.

Significance: The present investigation identified S_a, S_dr, S_tr, S_sk, S_pd and S_pc as minimum parameter panel for discriminative oral implant surface characterization. The widespread use of such a panel combined with biological data will help to identify cell-relevant implant surface structures, thus enabling the design of oral implants with predefined biological response.