A massively multi-scale approach to characterizing tissue architecture by synchrotron micro-CT applied to the human placenta
AuthorsTun, W. M.; orcid: 0000-0003-0991-8785
Poologasundarampillai, G.; orcid: 0000-0002-8498-323X
King, O. N. F.; orcid: 0000-0002-6152-7207
Basham, M.; orcid: 0000-0002-8438-1415
Lewis, R. M.; orcid: 0000-0003-4044-9104
Johnstone, E. D.
Brownbill, P.; orcid: 0000-0002-8328-7072
Darrow, M.; orcid: 0000-0001-6259-1684
Chernyavsky, I. L.; orcid: 0000-0003-0284-9318
MetadataShow full item record
AbstractMulti-scale structural assessment of biological soft tissue is challenging but essential to gain insight into structure–function relationships of tissue/organ. Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced imaging and robust, validated machine-learning segmentation techniques to provide the first massively multi-scale and multi-domain information that enables detailed morphological and functional analyses of both maternal and fetal placental domains. Finally, we quantify the scale-dependent error in morphological metrics of heterogeneous placental tissue, estimating the minimal tissue scale needed in extracting meaningful biological data. The developed protocol is beneficial for high-throughput investigation of structure–function relationships in both normal and diseased placentas, allowing us to optimize therapeutic approaches for pathological pregnancies. In addition, the methodology presented is applicable in the characterization of tissue architecture and physiological behaviours of other complex organs with similarity to the placenta, where an exchange barrier possesses circulating vascular and avascular fluid spaces.
CitationJournal of The Royal Society Interface, volume 18, issue 179, page 20210140
PublisherThe Royal Society
DescriptionFrom Crossref journal articles via Jisc Publications Router
History: epub 2021-06-02
Publication status: Published
Funder: Engineering and Physical Sciences Research Council; FundRef: 10.13039/501100000266; Grant(s): EP/T008725/1, EP/M023877/1
Funder: Wellcome Trust; FundRef: 10.13039/100010269; Grant(s): 212980/Z/18/Z
Funder: Great Britain Sasakawa Foundation; FundRef: 10.13039/501100000625
Funder: Medical Research Council; Grant(s): MR/N011538/1
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