Methodologies for assessing local surface texture features that are relevant to cell attachment

Abstract

In this paper, we describe techniques for extracting features from surface topography data, gathered by a 3D-microscopy system, on a length scale that is relevant for cell attachment. The feature parameters considered include standard surface roughness parameters applied to the complete surface as well as new feature parameters designed to quantify local variations in surface topography potentially influencing cell behaviour. Methodologies have been developed both to determine the degree of homogeneity or isotropy of a surface and to compare the topographies of different samples. The approaches followed include wavelet decomposition and linear and nonlinear filtering techniques. The analysis has been used to investigate the correlation between osteoblast cell attachment and structural features of titanium-coated surfaces representative of orthopaedic implants. The results confirm that there is a discernible correlation between cell orientation and the underlying surface lay.