Towards a clinically-based common coordinate framework for the human gut cell atlas: the gut models.
Common coordinate framework
Human cell atlas
Human gut cell atlas
Journal
BMC medical informatics and decision making
ISSN: 1472-6947
Titre abrégé: BMC Med Inform Decis Mak
Pays: England
ID NLM: 101088682
Informations de publication
Date de publication:
15 02 2023
15 02 2023
Historique:
received:
30
06
2022
accepted:
13
01
2023
entrez:
16
2
2023
pubmed:
17
2
2023
medline:
18
2
2023
Statut:
epublish
Résumé
The Human Cell Atlas resource will deliver single cell transcriptome data spatially organised in terms of gross anatomy, tissue location and with images of cellular histology. This will enable the application of bioinformatics analysis, machine learning and data mining revealing an atlas of cell types, sub-types, varying states and ultimately cellular changes related to disease conditions. To further develop the understanding of specific pathological and histopathological phenotypes with their spatial relationships and dependencies, a more sophisticated spatial descriptive framework is required to enable integration and analysis in spatial terms. We describe a conceptual coordinate model for the Gut Cell Atlas (small and large intestines). Here, we focus on a Gut Linear Model (1-dimensional representation based on the centreline of the gut) that represents the location semantics as typically used by clinicians and pathologists when describing location in the gut. This knowledge representation is based on a set of standardised gut anatomy ontology terms describing regions in situ, such as ileum or transverse colon, and landmarks, such as ileo-caecal valve or hepatic flexure, together with relative or absolute distance measures. We show how locations in the 1D model can be mapped to and from points and regions in both a 2D model and 3D models, such as a patient's CT scan where the gut has been segmented. The outputs of this work include 1D, 2D and 3D models of the human gut, delivered through publicly accessible Json and image files. We also illustrate the mappings between models using a demonstrator tool that allows the user to explore the anatomical space of the gut. All data and software is fully open-source and available online. Small and large intestines have a natural "gut coordinate" system best represented as a 1D centreline through the gut tube, reflecting functional differences. Such a 1D centreline model with landmarks, visualised using viewer software allows interoperable translation to both a 2D anatomogram model and multiple 3D models of the intestines. This permits users to accurately locate samples for data comparison.
Sections du résumé
BACKGROUND
The Human Cell Atlas resource will deliver single cell transcriptome data spatially organised in terms of gross anatomy, tissue location and with images of cellular histology. This will enable the application of bioinformatics analysis, machine learning and data mining revealing an atlas of cell types, sub-types, varying states and ultimately cellular changes related to disease conditions. To further develop the understanding of specific pathological and histopathological phenotypes with their spatial relationships and dependencies, a more sophisticated spatial descriptive framework is required to enable integration and analysis in spatial terms.
METHODS
We describe a conceptual coordinate model for the Gut Cell Atlas (small and large intestines). Here, we focus on a Gut Linear Model (1-dimensional representation based on the centreline of the gut) that represents the location semantics as typically used by clinicians and pathologists when describing location in the gut. This knowledge representation is based on a set of standardised gut anatomy ontology terms describing regions in situ, such as ileum or transverse colon, and landmarks, such as ileo-caecal valve or hepatic flexure, together with relative or absolute distance measures. We show how locations in the 1D model can be mapped to and from points and regions in both a 2D model and 3D models, such as a patient's CT scan where the gut has been segmented.
RESULTS
The outputs of this work include 1D, 2D and 3D models of the human gut, delivered through publicly accessible Json and image files. We also illustrate the mappings between models using a demonstrator tool that allows the user to explore the anatomical space of the gut. All data and software is fully open-source and available online.
CONCLUSIONS
Small and large intestines have a natural "gut coordinate" system best represented as a 1D centreline through the gut tube, reflecting functional differences. Such a 1D centreline model with landmarks, visualised using viewer software allows interoperable translation to both a 2D anatomogram model and multiple 3D models of the intestines. This permits users to accurately locate samples for data comparison.
Identifiants
pubmed: 36793076
doi: 10.1186/s12911-023-02111-9
pii: 10.1186/s12911-023-02111-9
pmc: PMC9933383
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
36Informations de copyright
© 2023. The Author(s).
Références
Genetics. 2022 Apr 4;220(4):
pubmed: 35166825
Nat Cell Biol. 2021 Nov;23(11):1117-1128
pubmed: 34750582
Cell. 2019 Dec 12;179(7):1455-1467
pubmed: 31835027
Nat Neurosci. 2021 Apr;24(4):584-594
pubmed: 33723434
Nature. 2012 Sep 20;489(7416):391-399
pubmed: 22996553
Nature. 2021 Sep;597(7875):250-255
pubmed: 34497389
J Biomed Inform. 2003 Dec;36(6):478-500
pubmed: 14759820
Scand J Immunol. 2020 Dec;92(6):e12990
pubmed: 33119150
Clin Transl Med. 2022 Mar;12(3):e694
pubmed: 35352511
Dis Mon. 2018 Feb;64(2):20-57
pubmed: 28826742
Am J Physiol Lung Cell Mol Physiol. 2017 Nov 1;313(5):L733-L740
pubmed: 28798251
Nucleic Acids Res. 2022 Jan 7;50(D1):D129-D140
pubmed: 34850121
Elife. 2017 Dec 05;6:
pubmed: 29206104
Gastroenterology. 2021 Dec;161(6):1842-1852.e10
pubmed: 34389338
Inflamm Bowel Dis. 2016 Feb;22(2):345-54
pubmed: 26717318
Nature. 2019 Oct;574(7777):187-192
pubmed: 31597973
Gut. 2019 Nov;68(11):1953-1960
pubmed: 31300515
Bioessays. 1992 Jul;14(7):501-2
pubmed: 1445290
J Biomed Semantics. 2014 May 19;5:21
pubmed: 25009735
J Biomed Semantics. 2013 Oct 08;4(1):22
pubmed: 24103658
J Biomed Semantics. 2016 Jul 04;7(1):44
pubmed: 27377652
J Anat. 2010 Oct;217(4):289-99
pubmed: 20979583
Genetics. 2022 Apr 4;220(4):
pubmed: 35266522
J Biomed Semantics. 2014 Aug 11;5:34
pubmed: 25140222
Front Cardiovasc Med. 2020 Mar 13;7:29
pubmed: 32232057
Gut. 2019 Dec;68(Suppl 3):s1-s106
pubmed: 31562236
Nat Commun. 2021 Sep 28;12(1):5675
pubmed: 34584087
Nature. 2019 Aug;572(7768):199-204
pubmed: 31292543
Lancet Gastroenterol Hepatol. 2020 Jan;5(1):17-30
pubmed: 31648971
Genesis. 2013 May;51(5):365-71
pubmed: 23355415
Eur J Gastroenterol Hepatol. 1997 Apr;9(4):353-9
pubmed: 9160197
BMJ. 2021 Jul 14;374:n1554
pubmed: 34261638
Mamm Genome. 2015 Oct;26(9-10):431-40
pubmed: 26296321