Literature DB >> 25701139

Spatial distribution of intracortical porosity varies across age and sex.

Jasmine A Nirody1, Karen P Cheng2, Robin M Parrish3, Andrew J Burghardt4, Sharmila Majumdar5, Thomas M Link6, Galateia J Kazakia7.   

Abstract

Cortical bone porosity is a major determinant of strength, stiffness, and fracture toughness of cortical tissue. The goal of this work was to investigate changes in spatial distribution and microstructure of cortical porosity associated with aging in men and women. The specific aims were to: 1) develop an automated technique for spatial analysis of cortical microstructure based on HR-pQCT data, and; 2) apply this technique to explore sex- and age-specific spatial distribution and microstructure of porosity within the cortex. We evaluated HR-pQCT images of the distal tibia from a cross-sectional cohort of 145 individuals, characterizing detectable pores as being in the endosteal, midcortical, or periosteal layers of the cortex. Metrics describing porosity, pore number, and pore size were quantified within each layer and compared across sexes, age groups, and cortical layers. The elderly cohort (65-78 years, n=22) displayed higher values than the young cohort (20-29 years, n=29) for all parameters both globally and within each layer. While all three layers displayed significant age-related porosity increases, the greatest difference in porosity between the young and elderly cohort was in the midcortical layer (+344%, p<0.001). Similarly, the midcortical layer reflected the greatest differences between young and elderly cohorts in both pore number (+243%, p<0.001) and size (+28%, p<0.001). Females displayed greater age-related changes in porosity and pore number than males. Females and males displayed comparable small to non-significant changes with age in pore size. In summary, considerable variability exists in the spatial distribution of detectable cortical porosity at the distal tibia, and this variability is dependent on age and sex. Intracortical pore distribution analysis may ultimately provide insight into both mechanisms of pore network expansion and biomechanical consequences of pore distribution.
Copyright © 2015. Published by Elsevier Inc.

Entities:  

Keywords:  Aging; Cortical bone; Gender; HR-pQCT; Porosity; Spatial distribution

Mesh:

Year:  2015        PMID: 25701139      PMCID: PMC4454740          DOI: 10.1016/j.bone.2015.02.006

Source DB:  PubMed          Journal:  Bone        ISSN: 1873-2763            Impact factor:   4.398


  39 in total

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Authors:  V Bousson; A Meunier; C Bergot; E Vicaut; M A Rocha; M H Morais; A M Laval-Jeantet; J D Laredo
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