Scientific Reports (Jan 2022)
Effect of data binning and frame averaging for micro-CT image acquisition on the morphometric outcome of bone repair assessment
Abstract
Abstract Despite the current advances in micro-CT analysis, the influence of some image acquisition parameters on the morphometric assessment outcome have not been fully elucidated. The aim of this study was to determine whether data binning and frame averaging affect the morphometric outcome of bone repair assessment using micro-CT. Four Wistar rats’ tibiae with a surgically created bone defect were imaged with micro-CT six times each, frame averaging set to 1 and 2, and data binning set to 1, 2 and 4, for each of the averaging values. Two-way ANOVA followed by Bonferroni tests assessed the significance of frame averaging and data binning on a set of morphometric parameters assessed in the image volumes (p < 0.01). The effect of frame averaging was not significant for any of the assessed parameters. Increased data binning led to larger trabecular thickness. In contrast, smaller bone volume fraction and bone volume were found as data binning increased. Trabeculae number and trabecular separation were not influenced by any of the parameters. In conclusion, the morphometric outcome of bone repair assessment in micro-CT demonstrated dependency upon data binning, but not frame averaging. Therefore, image acquisition of small anatomical structures (e.g., rat trabeculae) should be performed without data binning.