Age-Related Changes in Vertebral Morphometry by Statistical Shape Analysis

The morphological changes of the vertebrae associated with normal aging are still subject of debate, whereas this knowledge is important in detecting vertebral fractures and degenerative shape changes. The aim of this study is to present a method to statistically analyze the vertebral shape and dete...

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Bibliographic Details
Published inMesh Processing in Medical Image Analysis 2012 pp. 30 - 39
Main Authors Whitmarsh, Tristan, Del Río Barquero, Luis M., Di Gregorio, Silvana, Sierra, Jorge Malouf, Humbert, Ludovic, Frangi, Alejandro F.
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2012
SeriesLecture Notes in Computer Science
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Summary:The morphological changes of the vertebrae associated with normal aging are still subject of debate, whereas this knowledge is important in detecting vertebral fractures and degenerative shape changes. The aim of this study is to present a method to statistically analyze the vertebral shape and determining the morphometric changes related to normal aging. The analysis is performed on the L2 lumbar vertebrae from a large dataset of Computed Tomography scans. The surface meshes of all vertebrae, with a groupwise vertex correspondence between them, are first acquired by an intensity based registration process onto a segmented reference. Principal component analysis then reduces the dimensionality to the main modes of variation which were subsequently analyzed by multiple linear regression to acquire the global shape variations with respect to the age of the subjects. In addition, the correlation with age of the deformation at each mesh vertex is analyzed, giving a significance map of the age related changes. This analysis shows several shape changes which are in agreement with previous studies while also giving a more detailed global shape analysis. Understanding the normal shape changes allows for a better diagnosis of vertebral fractures and spinal pathologies.
ISBN:9783642334627
3642334628
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-33463-4_4