Abstract
Abstract
Quantifying the inner structure of bones is central to various analyses dealing with the phenotypic evolution of animals with an ossified skeleton. Computed tomography allows to assess the repartition of bone tissue within an entire skeletal element. Two parameters of importance for such analyses are the global compactness (Cg) and total cross-sectional area (Tt.Ar). However, no open-source, time-efficient methods are available to acquire these parameters for whole bones. A methodology to assess the variation of these parameters along a profile following one of the studied bone’s anatomical axes is also wanting. Here I present an ImageJ macro and associated R script to automatically acquire Cg and Tt.Ar along an axis of the skeletal element of interest using a slice-by-slice approach. No manual segmentation is required and several bones can be present on the analysed scan, as long as the bone of interest is isolated and the largest element on each slice. While some bias might be involved by the automatic acquisition, semi-automatic slice exclusion and correction procedures can be used to efficiently account for it. As a test case, µCT-data was gathered for the mid-lumbar vertebra of over 70 mammals. The two evaluated correction procedures proved to perform equally well, with a slight advantage for the one relying on the exclusion of local outliers. The presented macro allows to efficiently build a dataset concerned with the quantification of bone inner structure. The code being readily available, further improvement of the methodology and adjustment to particular needs can be easily performed.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Springer Science and Business Media LLC
Subject
Ecology, Evolution, Behavior and Systematics
Cited by
8 articles.
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