Morphometric staging of organ development based on cross sectional images
•An objective staging of developing organs is essential in systems biological studies.•We propose a novel method for staging based on cross sectional morphologies.•The method is validated by applying it to data on forebrain and limb development. An objective, continuous, and robust method for stagin...
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Veröffentlicht in: | Journal of theoretical biology 2018-03, Vol.440, p.80-87 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •An objective staging of developing organs is essential in systems biological studies.•We propose a novel method for staging based on cross sectional morphologies.•The method is validated by applying it to data on forebrain and limb development.
An objective, continuous, and robust method for staging developing embryos or organs is essential for providing a common measure of time when studying quantitative/systems developmental biology. However, classical methods based on factors such as somite number or qualitative visual attributes are discrete and/or ambiguous due to observers’ subjectivity. Thus, an alternative staging method based on an explicit and continuous description of developmental states over time, such as anatomy/morphology, is needed. Here, we briefly propose a novel staging method as a natural extension of classical staging based on cross sectional images of organs, which are more accessible than full 3D structures. The contours are represented as 2D closed curves and quantified using elliptic Fourier descriptors. Treating the ambiguity in classical staging as a statistical model, the relationship between the novel morphometric staging and classical staging can be determined. This method was validated by applying it to two different sets of data: chick forebrain and Xenopus hindlimb development. Using this method, it is also possible to reconstruct the time evolution of the average morphology, which would be useful for quantitatively comparing morphologies between embryos or between normal and abnormal conditions. |
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ISSN: | 0022-5193 1095-8541 |
DOI: | 10.1016/j.jtbi.2017.12.020 |