The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

Abstract

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand-wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index.

Statistical shape analysis of hand and wrist in paediatric population on radiographs

“…Landmarks(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) on the left-hand radiography used in this study were shown.…”

“…A significant innovation in analysing skeletal maturation is concerned with the way in which shape and size are characterised [5,6]. New methodologies and concepts, which are known collectively as geometric morphometrics, are being increasingly used in evolutionary contexts, since they make it possible to distinguish between a component of size change over time (growth) and one of shape change over time (development).…”

“…Most of the studies in medicine are concerned with the examination of geometric properties of anatomical structure [7]. Qualitative or quantitative datasets in the statistical analysis have commonly consisted of measuring values, and today's anatomical structure shape or appearance has begun to be used as input data with the development in imaging techniques [5][6][7][8][9].…”