Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
07 11 2023
07 11 2023
Historique:
received:
11
05
2023
accepted:
26
10
2023
medline:
9
11
2023
pubmed:
8
11
2023
entrez:
7
11
2023
Statut:
epublish
Résumé
Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to limits of time, prohibitive cost, or health concerns of repeat radiologic imaging. In contrast, cross-sectional samples have few such drawbacks, but it is not known how well estimates of growth milestones can be obtained from cross-sectional samples. The Craniofacial Growth Consortium Study (CGCS) contains longitudinal growth data for approximately 2000 individuals. Single samples from the CGCS for individuals representing cross-sectional data were used to test the ability to predict growth parameters in linear trait measurements separately by sex. Testing across a range of cross-sectional sample sizes from 5 to the full sample, we found that means from repeated samples were able to approximate growth rates determined from the full longitudinal CGCS sample, with mean absolute differences below 1 mm at cross-sectional sample sizes greater than ~ 200 individuals. Our results show that growth parameters and milestones can be accurately estimated from cross-sectional data compared to population-level estimates from complete longitudinal data, underscoring the utility of such datasets in growth modeling. This method can be applied to other forms of growth (e.g., stature) and to cases in which repeated radiographs are not feasible (e.g., cone-beam CT).
Identifiants
pubmed: 37935807
doi: 10.1038/s41598-023-46018-x
pii: 10.1038/s41598-023-46018-x
pmc: PMC10630296
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
19294Subventions
Organisme : NIDCR NIH HHS
ID : R01 DE024732
Pays : United States
Organisme : NIDCR NIH HHS
ID : R03 DE021435
Pays : United States
Informations de copyright
© 2023. The Author(s).
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