A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography

The characterization of developmental phenotypes often relies on the accurate linear measurement of structures that are small and require laborious preparation. This is tedious and prone to errors, especially when repeated for the multiple replicates that are required for statistical analysis, or when multiple distinct structures have to be analysed. To address this issue, we have developed a pipeline for characterization of long-bone length using micro-CT scans. It involves a semi-automated algorithm that uses the Mimics Innovation Suite package (Materialise) for automatic thresholding and fast interactive isolation and 3D-model generation of the main limb bones. All the image-processing steps are included in a user-friendly Python script. We show that the appropriate combination of scanning and in silico analysis conditions yields fast and reproducible length results, highly correlated with the measurements obtained via ex vivo skeletal preparations. Moreover, since micro-CT is not destructive, the samples can be used afterwards for histology or other applications. Our new pipeline will help developmental biologists and evolution researchers to achieve fast, reproducible and non-destructive length measurement of bone samples from multiple animal species. Summary statement Beltran Diaz et al. present a semi-automated pipeline for fast and versatile characterization of bone length from micro-CT images of mouse developmental samples.