Yang YM, Lee J, Kim YI, Cho BH, Park SB. Axial cervical vertebrae-based multivariate regression model for the estimation of skeletal-maturation status.
Orthod Craniofac Res 2014;
17:187-96. [PMID:
24720438 DOI:
10.1111/ocr.12045]
[Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2014] [Indexed: 11/29/2022]
Abstract
OBJECTIVES
This study aimed to determine the viability of using axial cervical vertebrae (ACV) as biological indicators of skeletal maturation and to build models that estimate ossification level with improved explanatory power over models based only on chronological age.
MATERIALS AND METHODS
The study population comprised 74 female and 47 male patients with available hand-wrist radiographs and cone-beam computed tomography images. Generalized Procrustes analysis was used to analyze the shape, size, and form of the ACV regions of interest. The variabilities of these factors were analyzed by principal component analysis. Skeletal maturation was then estimated using a multiple regression model.
RESULTS
Separate models were developed for male and female participants. For the female estimation model, the adjusted R(2) explained 84.8% of the variability of the Sempé maturation level (SML), representing a 7.9% increase in SML explanatory power over that using chronological age alone (76.9%). For the male estimation model, the adjusted R(2) was over 90%, representing a 1.7% increase relative to the reference model.
CONCLUSIONS
The simplest possible ACV morphometric information provided a statistically significant explanation of the portion of skeletal-maturation variability not dependent on chronological age. These results verify that ACV is a strong biological indicator of ossification status.
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