title: Age- and gender-related differences in cortical geometry and microstructure: Improved sensitivity by regional analysis.
abstract: OBJECTIVE
  While the importance of cortical structure quantification is increasingly underscored by recent literature, conventional analysis techniques obscure potentially important regional variations in cortical structure. The objective of this study was to characterize the spatial variability in cortical geometry and microstructure at the distal radius and tibia using high resolution peripheral quantitative computed tomography (HR-pQCT). We show that spatially-resolved analysis is able to identify cortical sub-regions with increased sensitivity to the effects of gender and aging.
  
  
  METHODS
  HR-pQCT scans of 146 volunteers (92 female/54 male) spanning a wide range of ages (20-78years) were analyzed. For each subject, radius and tibia scans were obtained using a clinical HR-pQCT system. Measures describing geometry (cortical bone thickness (Ct.Th)), microstructure (porosity (Ct.Po), pore diameter (Ct.Po.Dm), and pore size heterogeneity (Ct.Po.Dm SD)), and cortical bone density were calculated from the image data. Biomechanical parameters describing load and stress distribution were calculated using linear finite element analysis. Cortical quadrants were defined based on anatomic axes to quantify regional parameter variation. Subjects were categorized by gender, and age, and menopausal status for analysis.
  
  
  RESULTS
  Significant regional variation was found in all geometric and microstructural parameters in both the radius and tibia. In general, the radius showed more pronounced and significant variations in all parameters as compared with the tibia. At both sites, Ct.Po displayed the greatest regional variations. Correlation coefficients for Ct.Po and Ct.Th with respect to load and stress distribution provided evidence of an association between regional cortical structure and biomechanics in the tibia. Comparing women to men, differences in Ct.Po were most pronounced in the anterior quadrant of the radius (36% lower in women (p<0.01)) and the posterior quadrant of the tibia (27% lower in women (p<0.01)). Comparing elderly to young women, differences in Ct.Po were most pronounced in the lateral quadrant of the radius (328% higher in elderly women (p<0.001)) and the anterior quadrant of the tibia (433% higher in elderly women (p<0.001)). Comparing elderly to young men, the most pronounced age differences were found in the anterior radius (205% higher in elderly men, (p<0.001)) and the anterior tibia (190% higher in elderly men (p<0.01)). All subregional Ct.Po differences provided greater sensitivity to gender and age effects than those based on the global means.
  
  
  CONCLUSIONS
  These results show significant regional variation in all geometric and microarchitectural parameters studied in both the radius and tibia. Quantification of region-specific parameters provided increased sensitivity in the analysis of age- and gender-related differences, in many cases providing statistically significant differentiation of groups where conventional global analysis failed to detect differences. These results suggest that regional analysis may be important in studies of disease and therapeutic effects, particularly where microstructural parameters based on global analyses have thus far failed to identify a response in bone quality.
authors.affiliation: Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA. galateia.kazakia@ucsf.edu
authors.forename: Galateia J
authors.initials: GJ
authors.lastname: Kazakia
authors.forename: Jasmine A
authors.initials: JA
authors.lastname: Nirody
authors.forename: Gregory
authors.initials: G
authors.lastname: Bernstein
authors.forename: Miki
authors.initials: M
authors.lastname: Sode
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Burghardt
authors.forename: Sharmila
authors.initials: S
authors.lastname: Majumdar
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging / Q000502:physiology*; D001696:Biomechanical Phenomena / Q000502:physiology; D005260:Female; D020342:Finite Element Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D016062:Porosity; D011884:Radius / Q000033:anatomy & histology* / Q000000981:diagnostic imaging / Q000502:physiology; D012727:Sex Characteristics; D018709:Statistics, Nonparametric; D013977:Tibia / Q000033:anatomy & histology* / Q000000981:diagnostic imaging / Q000502:physiology; D014057:Tomography, X-Ray Computed; D055815:Young Adult