@article{2990491, title = "Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy", author = "Kournetas, N. and Spintzyk, S. and Schweizer, E. and Sawada, T. and Said, F. and Schmid, P. and Geis-Gerstorfer, J. and Eliades, G. and Rupp, F.", journal = "DENTAL MATERIALS", year = "2017", volume = "33", number = "8", pages = "e317-e327", publisher = "ELSEVIER SCIENCE INC 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA", issn = "0109-5641", doi = "10.1016/j.dental.2017.04.020", keywords = "Electron microscopy; Interferometry; Scanning electron microscopy; Surface roughness, Comparative evaluations; Optical interferometry; Raw data; Roughness analysis; Statistical approach; Statistical differences; Surface evaluations; White-light interferometry, Dental prostheses, titanium, interferometry; light; scanning electron microscopy; surface property; tooth implant, Dental Implants; Interferometry; Light; Microscopy, Electron, Scanning; Surface Properties; Titanium", abstract = "Objective Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. Methods Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50 μm and 5 μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey–Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. Results The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. Significance This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges. © 2017 The Academy of Dental Materials" }