Purpose of review: Quantification of the morphology of osteocyte lacunae has become a powerful tool to investigate bone metabolism, pathologies and aging. This review will provide a brief overview of 2D and 3D imaging methods for the determination of lacunar shape, orientation, density, and volume. Deviations between 2D-based and 3D-based lacunar volume estimations are often not sufficiently addressed and may give rise to contradictory findings. Thus, the systematic error arising from 2D-based estimations of lacunar volume will be discussed, and an alternative calculation proposed. Further, standardized morphological parameters and best practices for sampling and segmentation are suggested.
Recent findings: We quantified the errors in reported estimation methods of lacunar volume based on 2D cross-sections, which increase with variations in lacunar orientation and histological cutting plane. The estimations of lacunar volume based on common practice in 2D imaging methods resulted in an underestimation of lacunar volume of up to 85% compared to actual lacunar volume in an artificial dataset. For a representative estimation of lacunar size and morphology based on 2D images, at least 400 lacunae should be assessed per sample.
Osteocyte lacunae imaging methods have to be carefully selected regarding the aim of the project. If 3D imaging is not possible, 2D-based volume estimations should only be performed for samples with known lacunar orientation and elongation using a cutting plane aligned with the longest lacuna axis. The currently proposed recommendations for sampling and thresholding aim to guide researchers towards more reliable experimental results for elongated lacunae. Further research is required to determine the influence of method-inherent factors (contrast, resolution), segmentation, but also lacuna shape on lacunar volume estimation in order to come to best practices and comparable results within the bone community.
Keywords: 3D Imaging; CLSM; Lacuna; Lacunar volume; Microct; Nanoct; Osteocyte; Synchrotron.
© 2024. The Author(s).